From 4a0bce7db7b3ebf3f8becff62c620b5f7f20dd74 Mon Sep 17 00:00:00 2001 From: Travis Thompson Date: Mon, 16 Oct 2023 13:16:30 -0400 Subject: [PATCH] More tests added. --- README.rst | 2 +- docs/api.rst | 2 + docs/changelog.rst | 42 + docs/index.rst | 1 + docs/jsonschema.rst | 165 +- docs/reporting.rst | 43 +- docs/tutorial.rst | 37 +- src/academic_tracker/__init__.py | 2 +- .../athr_srch_emails_and_reports.py | 69 +- src/academic_tracker/athr_srch_modularized.py | 3 +- src/academic_tracker/athr_srch_webio.py | 3 +- .../emails_and_reports_helpers.py | 21 +- src/academic_tracker/helper_functions.py | 49 +- .../ref_srch_emails_and_reports.py | 54 - src/academic_tracker/ref_srch_modularized.py | 25 +- src/academic_tracker/ref_srch_webio.py | 417 +- src/academic_tracker/tracker_schema.py | 5 +- src/academic_tracker/user_input_checking.py | 1 + src/academic_tracker/webio.py | 201 +- tests/fixtures.py | 11 +- tests/regen_intermediate_files_ref.py | 66 +- tests/test_athr_srch_emails_and_reports.py | 3 + tests/test_athr_srch_webio_no_internet.py | 8 - tests/test_citation_parsing.py | 1 + tests/test_emails_and_reports_helpers.py | 8 +- tests/test_helper_functions.py | 614 +-- tests/test_ref_srch_emails_and_reports.py | 19 +- tests/test_ref_srch_modularized.py | 33 +- tests/test_ref_srch_webio_no_internet.py | 267 +- tests/test_user_input_checking.py | 122 +- tests/test_webio_no_internet.py | 42 +- tests/testing_files/Crossref_merge.json | 332 +- tests/testing_files/Crossref_misc.json | 6 +- tests/testing_files/Google_Scholar_merge.json | 314 +- tests/testing_files/ORCID_merge.json | 34 +- tests/testing_files/PubMed_merge.json | 1510 +++--- .../PubMed_modified_to_save_no_PMCID.json | 2 +- .../athr_project_emails_tabular.json | 4 +- .../athr_srch_build_author_loop.txt | 64 +- .../athr_srch_summary_report.txt | 24 +- ...hr_srch_summary_report_custom_template.txt | 320 +- .../author_search/all/publication_dict.json | 2300 ++++---- .../author_search/all/running_pubs1.json | 1532 +++--- .../author_search/all/running_pubs2.json | 1535 +++--- .../author_search/all/running_pubs3.json | 1533 +++--- .../author_search/all/running_pubs4.json | 2471 ++++----- .../author_search/all/running_pubs5.json | 2471 ++++----- .../author_search/all/running_pubs6.json | 2300 ++++---- .../author_search/all/running_pubs7.json | 2300 ++++---- .../author_search/all/running_pubs8.json | 2300 ++++---- .../no_Crossref/publication_dict.json | 1558 +++--- .../no_Crossref/running_pubs1.json | 1532 +++--- .../no_Crossref/running_pubs2.json | 1535 +++--- .../no_Crossref/running_pubs3.json | 1533 +++--- .../no_Crossref/running_pubs4.json | 1533 +++--- .../no_Crossref/running_pubs5.json | 1558 +++--- .../no_Crossref/running_pubs6.json | 1558 +++--- .../no_Google_Scholar/publication_dict.json | 2473 ++++----- .../no_Google_Scholar/running_pubs1.json | 1532 +++--- .../no_Google_Scholar/running_pubs2.json | 1535 +++--- .../no_Google_Scholar/running_pubs3.json | 2473 ++++----- .../no_Google_Scholar/running_pubs4.json | 2473 ++++----- .../no_Google_Scholar/running_pubs5.json | 2473 ++++----- .../no_Google_Scholar/running_pubs6.json | 2473 ++++----- .../no_ORCID/publication_dict.json | 2468 ++++----- .../author_search/no_ORCID/running_pubs1.json | 1532 +++--- .../author_search/no_ORCID/running_pubs2.json | 1532 +++--- .../author_search/no_ORCID/running_pubs3.json | 2468 ++++----- .../author_search/no_ORCID/running_pubs4.json | 2468 ++++----- .../author_search/no_ORCID/running_pubs5.json | 2468 ++++----- .../author_search/no_ORCID/running_pubs6.json | 2468 ++++----- .../no_PubMed/publication_dict.json | 338 +- .../no_PubMed/running_pubs3.json | 308 +- .../no_PubMed/running_pubs4.json | 338 +- .../no_PubMed/running_pubs5.json | 338 +- .../no_PubMed/running_pubs6.json | 338 +- .../all/matching_key_for_citation1.json | 2 +- .../ref_search/all/publication_dict.json | 460 +- .../ref_search/all/running_pubs1.json | 457 +- .../ref_search/all/running_pubs2.json | 407 +- .../ref_search/all/running_pubs3.json | 460 +- .../ref_search/all/running_pubs4.json | 460 +- .../ref_search/all/tokenized_reference.json | 2 +- .../no_Crossref/publication_dict.json | 292 +- .../ref_search/no_Crossref/running_pubs1.json | 292 +- .../ref_search/no_Crossref/running_pubs2.json | 292 +- .../no_PubMed/publication_dict.json | 44 +- .../ref_search/no_PubMed/running_pubs1.json | 44 +- .../ref_search/no_PubMed/running_pubs2.json | 44 +- tests/testing_files/pub_dict_from_PMID.json | 2 +- tests/testing_files/publication_dict.json | 324 +- .../publication_dict_Hunter_old.json | 4655 ----------------- .../publication_dict_truncated.json | 64 +- .../publication_dict_truncated_old.json | 255 - .../pubs_by_author_dict_truncated_old.json | 62 - .../ref_srch_Crossref_pub_dict.json | 104 +- ...citations_Crossref_duplicate_citation.json | 4 + ...rch_keys_for_citations_Crossref_merge.json | 5 + ...r_citations_PubMed_duplicate_citation.json | 4 + ..._srch_keys_for_citations_PubMed_merge.json | 5 + .../ref_srch_publication_dict.json | 82 +- ...tion_dict_Crossref_duplicate_citation.json | 241 + ..._srch_publication_dict_Crossref_merge.json | 965 ++++ ...publication_dict_Crossref_title_match.json | 241 + ...cation_dict_PubMed_duplicate_citation.json | 253 + ...ef_srch_publication_dict_PubMed_merge.json | 965 ++++ ...h_publication_dict_PubMed_title_match.json | 253 + .../ref_srch_report_tabular1.csv | 328 +- .../ref_srch_report_tabular2.csv | 328 +- .../ref_srch_report_tabular3.csv | 10 +- .../ref_srch_report_tabular4.xlsx | Bin 9653 -> 6577 bytes tests/testing_files/ref_srch_report_test1.txt | 104 +- tests/testing_files/ref_srch_report_test2.txt | 104 +- tests/testing_files/solo_Crossref.json | 314 +- .../tokenized_citations_missing_ref_line.json | 3471 ++++++++++++ 115 files changed, 38726 insertions(+), 44664 deletions(-) create mode 100644 docs/changelog.rst delete mode 100644 tests/testing_files/publication_dict_Hunter_old.json delete mode 100644 tests/testing_files/publication_dict_truncated_old.json delete mode 100644 tests/testing_files/pubs_by_author_dict_truncated_old.json create mode 100644 tests/testing_files/ref_srch_keys_for_citations_Crossref_duplicate_citation.json create mode 100644 tests/testing_files/ref_srch_keys_for_citations_Crossref_merge.json create mode 100644 tests/testing_files/ref_srch_keys_for_citations_PubMed_duplicate_citation.json create mode 100644 tests/testing_files/ref_srch_keys_for_citations_PubMed_merge.json create mode 100644 tests/testing_files/ref_srch_publication_dict_Crossref_duplicate_citation.json create mode 100644 tests/testing_files/ref_srch_publication_dict_Crossref_merge.json create mode 100644 tests/testing_files/ref_srch_publication_dict_Crossref_title_match.json create mode 100644 tests/testing_files/ref_srch_publication_dict_PubMed_duplicate_citation.json create mode 100644 tests/testing_files/ref_srch_publication_dict_PubMed_merge.json create mode 100644 tests/testing_files/ref_srch_publication_dict_PubMed_title_match.json create mode 100644 tests/testing_files/tokenized_citations_missing_ref_line.json diff --git a/README.rst b/README.rst index 100cdfd..44eed64 100644 --- a/README.rst +++ b/README.rst @@ -124,7 +124,7 @@ and use the example there to create it initially. The add_authors command can he with building the Authors section if you already have a csv file with author information. A good tool to help track down pesky JSON syntax errors is `here `__. There are also examples in the `example_configs `__ -directory of the GitHub repo. There are also more example in the supplemental +directory of the GitHub repo. There are also more examples in the supplemental material of the paper https://doi.org/10.6084/m9.figshare.19412165. diff --git a/docs/api.rst b/docs/api.rst index dc695fd..a1f2da1 100644 --- a/docs/api.rst +++ b/docs/api.rst @@ -31,5 +31,7 @@ API :members: .. automodule:: academic_tracker.webio :members: +.. automodule:: academic_tracker.emails_and_reports_helpers + :members: diff --git a/docs/changelog.rst b/docs/changelog.rst new file mode 100644 index 0000000..8a078f3 --- /dev/null +++ b/docs/changelog.rst @@ -0,0 +1,42 @@ +Change Log +========== + +Version 2.0.0 +~~~~~~~~~~~~~ + +Changes +------- +In the 1.0.0 version each source was queried in a certain order and if later sources found the +same publicaiton as a previous one it was simply ignored. Now a best attempt is made to try and +merge information from the previous source with information from later sources. An additional +"queried_sources" attribute was added to the publication object created for each publication to +indicate all of the sources where the publication was found. It is a list field, and each source +is appended to it as it is found. + +Enhancements +------------ +A "references" attribute was added to the publication object for each publication and the references +for the publication will appear there if available. It is a list of objects that have the attributes +"citation", "title", "PMID", "PMCID", and "DOI". Fields that can't be determined will have a null value. + +More information is able to be obtained from PubMed, such as DOI author affiliations, and author ORCIDs. + +Collective authors can now be specified and are handled appropriately when present on information from +queried sources. + +All new publication attributes were added to the reporting and the documentation updated. + +The raw queries from each source can now be saved using the --save-all-queries option. An "all_results.json" +file will be saved in the output if the option is given. + +The --keep-duplicates option was added to reference_search. This allows the user to force the search +not to drop what it deems as duplicates. The default is that they are still dropped automatically, but +this option allows for an override when the program thinks, incorrectly, that 2 references are the same. + +Bug Fixes +--------- +Crossref publication dates will now have day and month when available. A bug made it so only the year +was captured even if month and day were available. + + + diff --git a/docs/index.rst b/docs/index.rst index e63a4a2..7784a24 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -23,6 +23,7 @@ Documentation index: api license todo + changelog Indices and tables diff --git a/docs/jsonschema.rst b/docs/jsonschema.rst index e9b81eb..eb9ec7d 100644 --- a/docs/jsonschema.rst +++ b/docs/jsonschema.rst @@ -136,7 +136,11 @@ to search for goes. Every author in this section will be queried during author_s The first_name and last_name attributes are for the author's first and last names respectively, and are used to validate that the author under search is the same -as the queried author. +as the queried author. There is a special type of author known as collective authors. +These are not individuals, but are instead a collective and are published that way. +Use the collective_name attribute to indicate that an author is a collective. This +attribute takes priority, so if it is present the author will be treated as a collective +author even if they have first_name and last_name attributes. pubmed_name_search is used as the query string when querying sources. This is so the user can specify exactly what to query rather than simply querying the first @@ -170,161 +174,12 @@ gen_reports_and_emails_auth Validating Schema ----------------- -.. code-block:: console - { - "$schema": "https://json-schema.org/draft/2020-12/schema", - "title": "Configuration JSON", - "description": "Input file that contains information for how the program should run.", - - "type": "object", - "properties": { - "project_descriptions" : { - "type": "object", - "minProperties": 1, - "additionalProperties": { - "type":"object", - "properties":{ - "grants": {"type": "array", "minItems":1, "items": {"type": "string", "minLength": 1}}, - "cutoff_year": {"type": "integer"}, - "affiliations": {"type": "array", "minItems":1, "items": {"type": "string", "minLength": 1}}, - "project_report": {"type": "object", - "properties":{ - "columns": {"type": "object", - "minProperties":1, - "additionalProperties": {"type": "string", "minLength":1}}, - "sort": {"type": "array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "separator":{"type":"string", "maxLength":1, "minLength":1}, - "column_order":{"type":"array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "file_format":{"type":"string", "enum":["csv", "xlsx"]}, - "filename":{"type":"string", "minLength":1}, - "template": {"type": "string", "minLength":1}, - "from_email": {"type": "string", "format": "email"}, - "cc_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "to_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "email_body": {"type": "string", "minLength":1}, - "email_subject": {"type": "string", "minLength":1},}, - "dependentRequired":{ - "from_email": ["email_body", "email_subject"], - "to_email": ["from_email", "email_body", "email_subject"]}}, - "collaborator_report": {"type": "object", - "properties":{ - "columns": {"type": "object", - "minProperties":1, - "additionalProperties": {"type": "string", "minLength":1}}, - "sort": {"type": "array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "separator":{"type":"string", "maxLength":1, "minLength":1}, - "column_order":{"type":"array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "file_format":{"type":"string", "enum":["csv", "xlsx"]}, - "filename":{"type":"string", "minLength":1}, - "template": {"type": "string", "minLength":1}, - "from_email": {"type": "string", "format": "email"}, - "cc_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "to_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "email_body": {"type": "string", "minLength":1}, - "email_subject": {"type": "string", "minLength":1},}, - "dependentRequired":{ - "from_email": ["email_body", "email_subject"], - "to_email": ["from_email", "email_body", "email_subject"]},}, - "authors": {"type": "array", "minItems":1, "items": {"type": "string", "minLength": 1}}, - }, - - "required": ["grants", "affiliations"] - } - }, - - "ORCID_search" : {"type":"object", - "properties": { - "ORCID_key": {"type": "string", "minLength":1}, - "ORCID_secret": {"type": "string", "minLength":1}}, - "required": ["ORCID_key", "ORCID_secret"]}, - "PubMed_search" : {"type":"object", - "properties": { - "PubMed_email": {"type": "string", "format":"email"}}, - "required":["PubMed_email"]}, - "Crossref_search" : {"type":"object", - "properties": { - "mailto_email": {"type": "string", "format":"email"}}, - "required":["mailto_email"]}, - "summary_report" : {"type": "object", - "properties":{ - "columns": {"type": "object", - "minProperties":1, - "additionalProperties": {"type": "string", "minLength":1}}, - "sort": {"type": "array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "separator":{"type":"string", "maxLength":1, "minLength":1}, - "column_order":{"type":"array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "file_format":{"type":"string", "enum":["csv", "xlsx"]}, - "filename":{"type":"string", "minLength":1}, - "template": {"type": "string", "minLength":1}, - "from_email": {"type": "string", "format": "email"}, - "cc_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "to_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "email_body": {"type": "string", "minLength":1}, - "email_subject": {"type": "string", "minLength":1},}, - "dependentRequired":{ - "from_email": ["email_body", "email_subject", "to_email"]}}, - "Authors" : { "type": "object", - "minProperties": 1, - "additionalProperties": { - "type": "object", - "properties":{ - "first_name": {"type": "string", "minLength":1}, - "last_name":{"type": "string", "minLength":1}, - "pubmed_name_search": {"type": "string", "minLength":1}, - "email":{"type": "string", "format":"email"}, - "ORCID":{"type": "string", "pattern":"^\d{4}-\d{4}-\d{4}-\d{3}[0,1,2,3,4,5,6,7,8,9,X]$"}, - "grants": {"type": "array", "minItems":1, "items": {"type": "string", "minLength": 1}}, - "cutoff_year": {"type": "integer"}, - "affiliations": {"type": "array", "minItems":1, "items": {"type": "string", "minLength": 1}}, - "scholar_id": {"type": "string", "minLength":1}, - "project_report": {"type": "object", - "properties":{ - "columns": {"type": "object", - "minProperties":1, - "additionalProperties": {"type": "string", "minLength":1}}, - "sort": {"type": "array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "separator":{"type":"string", "maxLength":1, "minLength":1}, - "column_order":{"type":"array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "file_format":{"type":"string", "enum":["csv", "xlsx"]}, - "filename":{"type":"string", "minLength":1}, - "template": {"type": "string", "minLength":1}, - "from_email": {"type": "string", "format": "email"}, - "cc_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "to_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "email_body": {"type": "string", "minLength":1}, - "email_subject": {"type": "string", "minLength":1},}, - "dependentRequired":{ - "from_email": ["email_body", "email_subject"], - "to_email": ["from_email", "email_body", "email_subject"]}}, - "collaborator_report": {"type": "object", - "properties":{ - "columns": {"type": "object", - "minProperties":1, - "additionalProperties": {"type": "string", "minLength":1}}, - "sort": {"type": "array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "separator":{"type":"string", "maxLength":1, "minLength":1}, - "column_order":{"type":"array", "uniqueItems":True, "items": {"type": "string", "minLength":1}, "minItems":1}, - "file_format":{"type":"string", "enum":["csv", "xlsx"]}, - "filename":{"type":"string", "minLength":1}, - "template": {"type": "string", "minLength":1}, - "from_email": {"type": "string", "format": "email"}, - "cc_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "to_email": {"type": "array", "items": {"type": "string", "format": "email"}}, - "email_body": {"type": "string", "minLength":1}, - "email_subject": {"type": "string", "minLength":1},}, - "dependentRequired":{ - "from_email": ["email_body", "email_subject"], - "to_email": ["from_email", "email_body", "email_subject"]},}, - }, - "required" : ["first_name", "last_name", "pubmed_name_search"] - - } - } - - }, - "required": ["project_descriptions", "ORCID_search", "PubMed_search", "Crossref_search", "Authors"] - } +.. literalinclude:: ../src/academic_tracker/tracker_schema.py + :start-at: config_schema + :end-before: ## config_end + :language: none + Example diff --git a/docs/reporting.rst b/docs/reporting.rst index 5e0469a..fb6ead2 100644 --- a/docs/reporting.rst +++ b/docs/reporting.rst @@ -78,20 +78,22 @@ Author Search ------------- The report for the author_search is built by looping over each project, each author associated with the project, each publication associated with the author, -and each author on the publication. The template for author_search has 4 sections, -1 for each loop (project_loop, author_loop, pub_loop, and pub_author_loop). Tags +and each author on the publication. The template for author_search has 5 sections, +1 for each loop (project_loop, author_loop, pub_loop, pub_author_loop, and reference_loop). Tags denote the beginning and end of each loop. The section determines when keywords in the template are replaced. Keywords inside -the pub_author_loop section are replaced for each author on the publication. +the pub_author_loop section are replaced for each author on the publication. Keywords +inside the reference loop section are replaced for each reference on the publication. Keywords inside the pub_loop section are replaced for each publication associated with the author. Keywords inside the author_loop are replaced for each author associated with the project. Keywords inside the project loop section are replaced for each project. The sections are expected to be nested inside of each other, -so the pub_author_loop tags should be inside the pub_loop tags, the pub_loop tags +so the pub_author_loop and reference_loop tags should be inside the pub_loop tags, the pub_loop tags should be inside the author_loop tags, and the author_loop tags should be inside -the project_loop tags. If they are not then the report will most likely not look -as expected. +the project_loop tags. The pub_author_loop and reference_loop are on the same level +and should not be nested within each other. Any incorrect nesting will most likely +cause the report not to look as expected. If specifying a tabular report using the "columns" attribute the loops are determined by what keywords are present. If there are keywords from the pub_author_loop in @@ -103,14 +105,16 @@ author. Reference Search ---------------- The report for the reference_search is built by looping over each publication matched -in the reference, and each author on the publication. The template has 2 sections, -1 for each loop (pub_loop and pub_author_loop). Tags denote the beginning and end +in the reference, and each author on the publication. The template has 3 sections, +1 for each loop (pub_loop, pub_author_loop, and reference_loop). Tags denote the beginning and end of each loop. The section determines when keywords in the template are replaced. Keywords inside the pub_author_loop section are replaced for each author on the -publication. Keywords inside the pub_loop section are replaced for each publication. -The sections are expected to be nested inside of each other, so the pub_author_loop -tags should be inside the pub_loop tags. If they are not then the report will -most likely not look as expected. +publication. Keywords inside the reference loop section are replaced +for each reference on the publication. Keywords inside the pub_loop section are replaced for each publication. +The sections are expected to be nested inside of each other, so the pub_author_loop and reference_loop +tags should be inside the pub_loop tags. The pub_author_loop and reference_loop are on the same level +and should not be nested within each other. Any incorrect nesting will most likely +cause the report not to look as expected. Project Report @@ -164,12 +168,13 @@ Keywords Will be replaced with a comma separated list of author names of all authors. Will be replaced with a comma separated list of grants associated with the publication. - Will be replaced with a comma separated list of the sources where information was found for the publication. + Will be replaced with a comma separated list of the sources where information was found for the publication. Pub Author Keywords - Pulled from the authors section of each publication in the publications.json file. + Some authors are a collective and have a special field for the name instead of first and last. @@ -177,9 +182,17 @@ Keywords Author Keywords - Pulled from the Authors section of the configuration JSON file. + Some authors are a collective and have a special field for the name instead of first and last. + Publication References Keywords + The full citation for the reference if available. + The reference title if available. + The reference PMID if available. + The reference PMCID if available. + The reference DOI if available. + Reference Search Specific Keywords The line from the reference file used to find the publication. The title parsed (tokenized) from the reference line. @@ -187,8 +200,8 @@ Keywords The PMID parsed (tokenized) from the reference line. The authors parsed (tokenized) from the reference line. Will be a comma separated list. If the publication is in the comparison file True otherwise False. - - + + Examples ~~~~~~~~ diff --git a/docs/tutorial.rst b/docs/tutorial.rst index 4838d2b..837d1db 100644 --- a/docs/tutorial.rst +++ b/docs/tutorial.rst @@ -27,7 +27,7 @@ Command Line Signature ---------------------- .. code-block:: console - academic_tracker author_search [--test --prev-pub= --no-GoogleScholar --no-ORCID --no-Crossref --no-PubMed --verbose --silent] + academic_tracker author_search [--test --prev-pub= --save-all-queries --no-GoogleScholar --no-ORCID --no-Crossref --no-PubMed --verbose --silent] Description @@ -51,7 +51,7 @@ The description of everything author_search does with the previous publications may seem arbitrary and confusing. The idea is that users will make an initial list of authors to keep track of and then run author_search every so often to look for new publications for them. To make this as easy as possible it is -neceessary to both have author_search look for previous publications automatically +necessary to both have author_search look for previous publications automatically and for the output to be cumulative so that the same publications are not reported multiple times. @@ -77,31 +77,37 @@ to tracker-test-YYMMDDHHMM and prevents any emails from being sent. Specifies a publications.json file to use as a list of publications to ignore when searching for new publications. Set to "ignore" to prevent author_search from automatically looking for a publications.json file in tracker directories. + +--save-all-queries: + +If used, all of the raw data returned from each source for each author will be saved +in a file called "all_results.json". The structure is {"source_name":{"author_id_1":[pub_dict_1, pub_dict_2, ...], ...}, ...} +Ex. {"PubMed":{"Hunter Moseley":[{}, ...]}, "Crossref":{"Hunter Moseley":[{}, ...]}, ...} --no-GoogleScholar: -If used author_search will not search Google Scholar for publications. +If used, author_search will not search Google Scholar for publications. --no-ORCID: -If used author_search will not search ORCID for publications. +If used, author_search will not search ORCID for publications. --no-Crossref: -If used author_search will not search Crossref for publications. +If used, author_search will not search Crossref for publications. --no-PubMed: -If used author_search will not search PubMed for publications. This option is +If used, author_search will not search PubMed for publications. This option is assumed if the PubMed_search section of the configuration JSON file is missing. --verbose: -If used HTML errors and other warnings will be printed to the screen. +If used, HTML errors and other warnings will be printed to the screen. --silent: -If used nothing will be printed to the screen. +If used, nothing will be printed to the screen. Outputs @@ -126,11 +132,14 @@ from_email is given then a file is created for every author that had new publica Details about reports can be found in the :doc:`reporting` section. +An all_results.json file will be output if the --save-all-queries option is given. + publications.json emails.json summary_report.txt projectname_project_report.txt projectname_authorname_project_report.txt +all_results.json Examples @@ -361,7 +370,7 @@ Command Line Signature ---------------------- .. code-block:: console - academic_tracker reference_search [--test --prev-pub= --PMID-reference --MEDLINE-reference --no-Crossref --no-PubMed --verbose --silent] + academic_tracker reference_search [--test --prev-pub= --save-all-queries --PMID-reference --MEDLINE-reference --no-Crossref --no-PubMed --verbose --silent] Description @@ -414,6 +423,13 @@ to tracker-test-YYMMDDHHMM and prevents any emails from being sent. Specifies a publications.json file to use as a list of publications to compare with when generating the summary report. + +--save-all-queries: + +If used, all of the raw data returned from each source for each author will be saved +in a file called "all_results.json". The structure is {"source_name":[[pub_dict_1, pub_dict_2, ...]], ...} +Ex. {"PubMed":[[{}, ...]], "Crossref":[[{}, ...]]} The index of each list in the source +lines up with the index in the tokenized_reference. --PMID-reference: @@ -460,10 +476,13 @@ If --PMID-reference is used no reports or emails are generated. Details about reports can be found in the :doc:`reporting` section. +An all_results.json file will be output if the --save-all-queries option is given. + publications.json tokenized_reference.json emails.json summary_report.txt +all_results.json Examples diff --git a/src/academic_tracker/__init__.py b/src/academic_tracker/__init__.py index 4c8b1c8..c9f6b77 100644 --- a/src/academic_tracker/__init__.py +++ b/src/academic_tracker/__init__.py @@ -39,4 +39,4 @@ This module contains general functions for interfacing with the internet. """ -__version__ = "1.0.6" +__version__ = "2.0.0" diff --git a/src/academic_tracker/athr_srch_emails_and_reports.py b/src/academic_tracker/athr_srch_emails_and_reports.py index 092c569..eb0f863 100644 --- a/src/academic_tracker/athr_srch_emails_and_reports.py +++ b/src/academic_tracker/athr_srch_emails_and_reports.py @@ -350,7 +350,7 @@ def create_tabular_collaborator_report(publication_dict, config_dict, author, pu temp_dict = {} for column_name, value in columns.items(): for keyword, pub_author_key in pub_authors_keyword_map.items(): - value = value.replace(keyword, str(pub_author[pub_author_key])) + value = value.replace(keyword, str(pub_author[pub_author_key]) if pub_author_key in pub_author else "None") temp_dict[column_name] = value collaborators.append(temp_dict) @@ -400,7 +400,7 @@ def create_collaborator_report(publication_dict, template, author, pubs, filenam pub_author_template_copy = pub_author_template for keyword, pub_author_key in pub_authors_keyword_map.items(): - pub_author_template_copy = pub_author_template_copy.replace(keyword, str(pub_author[pub_author_key])) + pub_author_template_copy = pub_author_template_copy.replace(keyword, str(pub_author[pub_author_key]) if pub_author_key in pub_author else "None") report += pub_author_template_copy @@ -644,70 +644,7 @@ def _build_report_rows(publication_dict, config_dict, authors_by_project_dict, p pub, None, None) - - - # ## If references or authors is an empty list then you get unexpected behavior where pubs just won't show up, - # ## so look for it before hand and just give it a null dictionary if it is empty. - # if not (references := publication_dict[pub]["references"]): - # references = [{ - # "PMCID": None, - # "citation": None, - # "doi": None, - # "pubmed_id": None, - # "title": None - # }] - # ## There should always be at least 1 author since this is specific to author search, but the code is here for completeness. - # if not (pub_authors := publication_dict[pub]["authors"]): - # pub_authors = [{ - # "ORCID": None, - # "affiliation": None, - # "author_id": None, - # "firstname": None, - # "initials": None, - # "lastname": None - # }] - - # if has_pub_author_keywords and has_reference_keywords: - # for pub_author in pub_authors: - # for reference in references: - # rows.append(emails_and_reports_helpers._replace_keywords(row_template, - # publication_dict, - # config_dict, - # project_name, - # author, - # pub, - # pub_author, - # reference)) - - # elif has_pub_author_keywords: - # for pub_author in pub_authors: - # rows.append(emails_and_reports_helpers._replace_keywords(row_template, - # publication_dict, - # config_dict, - # project_name, - # author, - # pub, - # pub_author)) - - # elif has_reference_keywords: - # for reference in references: - # rows.append(emails_and_reports_helpers._replace_keywords(row_template, - # publication_dict, - # config_dict, - # project_name, - # author, - # pub, - # {}, - # reference)) - - # else: - # rows.append(emails_and_reports_helpers._replace_keywords(row_template, - # publication_dict, - # config_dict, - # project_name, - # author, - # pub)) - + else: rows.append(emails_and_reports_helpers._replace_keywords(row_template, publication_dict, diff --git a/src/academic_tracker/athr_srch_modularized.py b/src/academic_tracker/athr_srch_modularized.py index 5f56f4a..ad08e7f 100644 --- a/src/academic_tracker/athr_srch_modularized.py +++ b/src/academic_tracker/athr_srch_modularized.py @@ -146,7 +146,8 @@ def build_publication_dict(config_dict, prev_pubs, no_ORCID, no_GoogleScholar, n for author, pub_list in all_queries["PubMed"].items(): new_list = [] for pub in pub_list: - new_list.append(helper_functions.create_pub_dict_for_saving_PubMed(pub, True)) + _, pub_dict = helper_functions.create_pub_dict_for_saving_PubMed(pub, True) + new_list.append(pub_dict) all_queries["PubMed"][author] = new_list return running_pubs, all_queries diff --git a/src/academic_tracker/athr_srch_webio.py b/src/academic_tracker/athr_srch_webio.py index 6f5598c..65b3ba0 100644 --- a/src/academic_tracker/athr_srch_webio.py +++ b/src/academic_tracker/athr_srch_webio.py @@ -69,8 +69,7 @@ def search_PubMed_for_pubs(running_pubs, authors_json, from_email, prev_query=No continue all_pubs[author].append(pub) - pub_dict = helper_functions.create_pub_dict_for_saving_PubMed(pub) - pub_id = pub_dict["doi"] if pub_dict["doi"] else pub_dict["pubmed_id"] + pub_id, pub_dict = helper_functions.create_pub_dict_for_saving_PubMed(pub) if matching_pub_id := helper_functions.get_pub_id_in_publication_dict(pub_id, pub.title, running_pubs): if "PubMed" in running_pubs[matching_pub_id]["queried_sources"]: diff --git a/src/academic_tracker/emails_and_reports_helpers.py b/src/academic_tracker/emails_and_reports_helpers.py index f44876d..7c4cc31 100644 --- a/src/academic_tracker/emails_and_reports_helpers.py +++ b/src/academic_tracker/emails_and_reports_helpers.py @@ -31,6 +31,7 @@ pub_authors_keyword_map = {"":"firstname", "":"lastname", "":"initials", + "": "collectivename", "":"affiliation", "":"ORCID", "":"author_id"} @@ -47,6 +48,7 @@ authors_keywords_map = {"":"first_name", "":"last_name", + "": "collective_name", "":"pubmed_name_search", "":"email"} @@ -137,7 +139,7 @@ def _replace_keywords(template, publication_dict, config_dict, ## Pub authors keywords if pub_author: for keyword, pub_author_key in pub_authors_keyword_map.items(): - template_copy[key] = template_copy[key].replace(keyword, str(pub_author[pub_author_key])) + template_copy[key] = template_copy[key].replace(keyword, str(pub_author[pub_author_key]) if pub_author_key in pub_author else "None") ## references keywords if reference: @@ -251,7 +253,22 @@ def _build_pub_author_and_reference_rows(publication_dict, config_dict, row_template, project_name="", author="", pub="", tokenized_citation=None, is_citation_in_prev_pubs=None): - """ + """Build rows for each pub_author and reference. + + Args: + publication_dict (dict): keys and values match the publications JSON file. + config_dict (dict): keys and values match the project tracking configuration JSON file. + has_pub_author_keywords (bool): if True, then row_template has keywords to replace that are attributes to publication authors. + has_reference_keywords (bool): if True, then row_template has keywords to replace that are attributes to publication references. + row_template (dict): keys are column names and values are what the elements of the column should be. + project_name (str): the name of the project to replace. + author (str): the key to the author in config_dict["Authors"]. + pub (str): the key to the pub in publication_dict. + tokenized_citation (dict|None): a tokenized citation from the reference for the publication. + is_citation_in_prev_pubs (bool|None): whether this publication is in the previous publications or not. If None then it isn't applicable. + + Returns: + rows (list): list of dictionaries meant to eventually be turned into a pandas DataFrame. """ rows = [] diff --git a/src/academic_tracker/helper_functions.py b/src/academic_tracker/helper_functions.py index db73123..560d037 100644 --- a/src/academic_tracker/helper_functions.py +++ b/src/academic_tracker/helper_functions.py @@ -193,13 +193,16 @@ def do_strings_fuzzy_match(string1, string2, match_ratio=90): """Fuzzy match the 2 strings and if the ratio is greater than or equal to match_ratio, return True. Args: - string1 (str): a string to fuzzy match. - string2 (str): a string to fuzzy match. + string1 (str|None): a string to fuzzy match. + string2 (str|None): a string to fuzzy match. match_ratio (int): the ratio (0-100) that the match must be greater than to return True. Returns: (bool): True if strings match, False otherwise. """ + if string1 is None or string2 is None: + return False + string1 = string1.lower() string2 = string2.lower() if fuzzywuzzy.fuzz.ratio(string1, string2) >= match_ratio or\ @@ -702,6 +705,7 @@ def create_pub_dict_for_saving_PubMed(pub, include_xml=False): include_xml (bool): if True, include the raw XML query in the key "xml". Returns: + pub_id (str): the ID of the publication (DOI or PMID). pub_dict (dict): pub converted to a dictionary. Keys are "pubmed_id", "title", "abstract", "keywords", "journal", "publication_date", "authors", "methods", "conclusions", "results", "copyrights", and "doi" """ @@ -714,7 +718,7 @@ def create_pub_dict_for_saving_PubMed(pub, include_xml=False): pub_dict["pubmed_id"] = None if (doi := pub_dict["xml"].find("PubmedData/ArticleIdList/ArticleId[@IdType='doi']")) is not None: - pub_dict["doi"] = DOI_URL + doi.text.lower() + pub_dict["doi"] = doi.text.lower() else: pub_dict["doi"] = None @@ -782,7 +786,7 @@ def create_pub_dict_for_saving_PubMed(pub, include_xml=False): orcid = None if (text := author.find("Identifier[@Source='ORCID']")) is not None: - orcid = regex_search_return(r"(\d{4}-\d{4}-\d{4}-\d{3}[0,1,2,3,4,5,6,7,8,9,X])", text.text)[0] + orcid = extract_ORCID_from_string(text.text) if collective_name: temp_dict = {"collectivename":collective_name, @@ -811,7 +815,9 @@ def create_pub_dict_for_saving_PubMed(pub, include_xml=False): else: pub_dict["publication_date"] = {"year":None, "month":None, "day":None} - return pub_dict + pub_id = DOI_URL + pub_dict["doi"] if pub_dict["doi"] else pub_dict["pubmed_id"] + + return pub_id, pub_dict @@ -823,8 +829,8 @@ def create_pub_dict_for_saving_Crossref(work, prev_query): prev_query (dict|None): a dictionary containing publications from a previous query, used for message printing. Returns: - pub_id (str): the ID of the publication (DOI, PMID, or URL). - pub_dict (dict): the standard pub_dict with values filled in from the Crossref publication. + pub_id (str|None): the ID of the publication (DOI, PMID, or URL). If None, an ID couldn't be determined. + pub_dict (dict|None): the standard pub_dict with values filled in from the Crossref publication. If None, an ID couldn't be determined. """ if "title" in work: title = work["title"][0] @@ -864,8 +870,7 @@ def create_pub_dict_for_saving_Crossref(work, prev_query): orcid = None if "ORCID" in cr_author_dict: - orcid = regex_search_return(r"(\d{4}-\d{4}-\d{4}-\d{3}[0,1,2,3,4,5,6,7,8,9,X])", - cr_author_dict["ORCID"])[0] + orcid = extract_ORCID_from_string(cr_author_dict["ORCID"]) temp_dict["ORCID"] = orcid temp_dict["author_id"] = None @@ -904,7 +909,7 @@ def create_pub_dict_for_saving_Crossref(work, prev_query): date_found = True if date_found: - date_length = len(work[date_key]["date-parts"]) + date_length = len(work[date_key]["date-parts"][0]) if date_length > 2: publication_year = work[date_key]["date-parts"][0][0] @@ -943,7 +948,7 @@ def create_pub_dict_for_saving_Crossref(work, prev_query): if "reference" in work: for reference in work["reference"]: if "DOI" in reference: - ref_doi = DOI_URL + reference["DOI"] + ref_doi = reference["DOI"] else: ref_doi = None @@ -980,6 +985,28 @@ def create_pub_dict_for_saving_Crossref(work, prev_query): +ORCID_regex = r"(\d{4}-\d{4}-\d{4}-\d{3}[0,1,2,3,4,5,6,7,8,9,X])" +alt_ORCID_regex = r"(\d{4}\d{4}\d{4}\d{3}[0,1,2,3,4,5,6,7,8,9,X])" +def extract_ORCID_from_string(string): + """Extract an ORCID ID from a string. + + Args: + string (str): the string to extract the ID from. + + Returns: + (str|None): either the extracted ID as a string or None. + """ + + if re_match := re.search(ORCID_regex, string): + return re_match.groups()[0] + elif re_match := re.search(alt_ORCID_regex, string): + captured_string = re_match.groups()[0] + new_string = captured_string[0:4] + '-' + captured_string[4:8] + '-' + captured_string[8:12] + '-' + captured_string[12:] + return new_string + else: + return None + + def is_fuzzy_match_to_list(str_to_match, list_to_match): """True if string is a 90 or higher ratio match to any string in list, False otherwise. diff --git a/src/academic_tracker/ref_srch_emails_and_reports.py b/src/academic_tracker/ref_srch_emails_and_reports.py index f52aa02..cf9d387 100644 --- a/src/academic_tracker/ref_srch_emails_and_reports.py +++ b/src/academic_tracker/ref_srch_emails_and_reports.py @@ -184,60 +184,6 @@ def create_tabular_report(publication_dict, config_dict, is_citation_in_prev_pub tokenized_citations[tok_index], is_citation_in_prev_pubs) - - - # ## If references or authors is an empty list then you get unexpected behavior where pubs just won't show up, - # ## so look for it before hand and just give it a null dictionary if it is empty. - # if not (references := publication_dict[pub]["references"]): - # references = [{ - # "PMCID": None, - # "citation": None, - # "doi": None, - # "pubmed_id": None, - # "title": None - # }] - # if not (pub_authors := publication_dict[pub]["authors"]): - # pub_authors = [{ - # "ORCID": None, - # "affiliation": None, - # "author_id": None, - # "firstname": None, - # "initials": None, - # "lastname": None - # }] - - # if has_pub_author_keywords and has_reference_keywords: - # for pub_author in pub_authors: - # for reference in references: - # rows.append(emails_and_reports_helpers._replace_keywords(row_template, - # publication_dict, - # None, - # pub=pub, - # tokenized_citation=tokenized_citations[tok_index], - # is_citation_in_prev_pubs=is_citation_in_prev_pubs, - # pub_author=pub_author, - # reference=reference)) - - # elif has_pub_author_keywords: - # for pub_author in pub_authors: - # rows.append(emails_and_reports_helpers._replace_keywords(row_template, - # publication_dict, - # None, - # pub=pub, - # tokenized_citation=tokenized_citations[tok_index], - # is_citation_in_prev_pubs=is_citation_in_prev_pubs, - # pub_author=pub_author)) - - # else: - # for reference in references: - # rows.append(emails_and_reports_helpers._replace_keywords(row_template, - # publication_dict, - # None, - # pub=pub, - # tokenized_citation=tokenized_citations[tok_index], - # is_citation_in_prev_pubs=is_citation_in_prev_pubs, - # reference=reference)) - else: rows.append(emails_and_reports_helpers._replace_keywords(row_template, publication_dict, diff --git a/src/academic_tracker/ref_srch_modularized.py b/src/academic_tracker/ref_srch_modularized.py index 9d4cea1..37af28a 100644 --- a/src/academic_tracker/ref_srch_modularized.py +++ b/src/academic_tracker/ref_srch_modularized.py @@ -93,32 +93,36 @@ def build_publication_dict(config_dict, tokenized_citations, no_Crossref, no_Pub if not no_PubMed: helper_functions.vprint("Searching PubMed.") running_pubs, PubMed_matching_key_for_citation, PubMed_publication_dict = \ - ref_srch_webio.search_references_on_PubMed(running_pubs, + ref_srch_webio.search_references_on_source("PubMed", + running_pubs, tokenized_citations, config_dict["PubMed_search"]["PubMed_email"]) all_queries["PubMed"] = PubMed_publication_dict if not no_Crossref: helper_functions.vprint("Searching Crossref.") running_pubs, Crossref_matching_key_for_citation, Crossref_publication_dict = \ - ref_srch_webio.search_references_on_Crossref(running_pubs, - tokenized_citations, - config_dict["Crossref_search"]["mailto_email"]) + ref_srch_webio.search_references_on_source("Crossref", + running_pubs, + tokenized_citations, + config_dict["Crossref_search"]["mailto_email"]) all_queries["Crossref"] = Crossref_publication_dict ## Do a second pass using the saved queries. if not no_PubMed: running_pubs, PubMed_matching_key_for_citation, PubMed_publication_dict = \ - ref_srch_webio.search_references_on_PubMed(running_pubs, + ref_srch_webio.search_references_on_source("PubMed", + running_pubs, tokenized_citations, config_dict["PubMed_search"]["PubMed_email"], all_queries["PubMed"]) if not no_Crossref: running_pubs, Crossref_matching_key_for_citation, Crossref_publication_dict = \ - ref_srch_webio.search_references_on_Crossref(running_pubs, - tokenized_citations, - config_dict["Crossref_search"]["mailto_email"], - all_queries["Crossref"]) + ref_srch_webio.search_references_on_source("Crossref", + running_pubs, + tokenized_citations, + config_dict["Crossref_search"]["mailto_email"], + all_queries["Crossref"]) matching_key_for_citation = [None] * len(tokenized_citations) @@ -136,7 +140,8 @@ def build_publication_dict(config_dict, tokenized_citations, no_Crossref, no_Pub for i, pub_list in enumerate(all_queries["PubMed"]): new_list = [] for pub in pub_list: - new_list.append(helper_functions.create_pub_dict_for_saving_PubMed(pub, True)) + _, pub_dict = helper_functions.create_pub_dict_for_saving_PubMed(pub, True) + new_list.append(pub_dict) all_queries["PubMed"][i] = new_list return running_pubs, tokenized_citations, all_queries diff --git a/src/academic_tracker/ref_srch_webio.py b/src/academic_tracker/ref_srch_webio.py index af9826c..6aaff81 100644 --- a/src/academic_tracker/ref_srch_webio.py +++ b/src/academic_tracker/ref_srch_webio.py @@ -50,11 +50,10 @@ def build_pub_dict_from_PMID(PMID_list, from_email): publications = pubmed.query(PMID_to_search, max_results=10) for pub in publications: + pub_id, pub_dict = helper_functions.create_pub_dict_for_saving_PubMed(pub) - pmid = pub.pubmed_id.split("\n")[0] - pub_id = DOI_URL + pub.doi.lower() if pub.doi else pmid - if pmid == PMID_to_search: - publication_dict[pub_id] = helper_functions.create_pub_dict_for_saving_PubMed(pub) + if pub_dict["pubmed_id"] == PMID_to_search: + publication_dict[pub_id] = pub_dict break time.sleep(1) @@ -63,192 +62,195 @@ def build_pub_dict_from_PMID(PMID_list, from_email): -def search_references_on_PubMed(running_pubs, tokenized_citations, from_email, prev_query=None): - """Searhes PubMed for publications matching the citations. +# def search_references_on_PubMed(running_pubs, tokenized_citations, from_email, prev_query=None): +# """Searhes PubMed for publications matching the citations. - For each citation in tokenized_citations PubMed is queried for the publication. - If the publication is already in running_pubs then missing information will be - filled in if possible. +# For each citation in tokenized_citations PubMed is queried for the publication. +# If the publication is already in running_pubs then missing information will be +# filled in if possible. - Args: - running_pubs (dict): dictionary of publications matching the JSON schema for publications. - tokenized_citations (list): list of citations parsed from a source. Each citation is a dict {"authors", "title", "DOI", "PMID", "reference_line", "pub_dict_key"}. - from_email (str): used in the query to PubMed. - prev_query (list|None): a list of lists containing publications from a previous call to this function. [[pub1, ...], [pub1, ...], ...] +# Args: +# running_pubs (dict): dictionary of publications matching the JSON schema for publications. +# tokenized_citations (list): list of citations parsed from a source. Each citation is a dict {"authors", "title", "DOI", "PMID", "reference_line", "pub_dict_key"}. +# from_email (str): used in the query to PubMed. +# prev_query (list|None): a list of lists containing publications from a previous call to this function. [[pub1, ...], [pub1, ...], ...] - Returns: - running_pubs (dict): keys are pulication ids and values are a dictionary with publication attributes - matching_key_for_citation (list): list of keys to the publication matching the citation at the same index - all_pubs (list): list of lists, each index is the pubs searched through after querying until the citation was matched - """ +# Returns: +# running_pubs (dict): keys are pulication ids and values are a dictionary with publication attributes +# matching_key_for_citation (list): list of keys to the publication matching the citation at the same index +# all_pubs (list): list of lists, each index is the pubs searched through after querying until the citation was matched +# """ - # initiate PubMed API - pubmed = pymed.PubMed(tool=TOOL, email=from_email) +# # initiate PubMed API +# pubmed = pymed.PubMed(tool=TOOL, email=from_email) - all_pubs = [] - matching_key_for_citation = [] +# all_pubs = [] +# matching_key_for_citation = [] - for i, citation in enumerate(tokenized_citations): - all_pubs.append([]) +# for i, citation in enumerate(tokenized_citations): +# all_pubs.append([]) - if citation["PMID"]: - query_string = citation["PMID"] - elif citation["DOI"]: - query_string = citation["DOI"] - elif citation["title"]: - query_string = citation["title"] - else: - matching_key_for_citation.append(None) - continue - publications = pubmed.query(query_string, max_results=10) if not prev_query else prev_query[i] +# if citation["PMID"]: +# query_string = citation["PMID"] +# elif citation["DOI"]: +# query_string = citation["DOI"] +# elif citation["title"]: +# query_string = citation["title"] +# else: +# matching_key_for_citation.append(None) +# continue +# publications = pubmed.query(query_string, max_results=10) if not prev_query else prev_query[i] - citation_matched_to_pub = False - for pub in publications: - if not isinstance(pub, pymed.article.PubMedArticle): - continue - all_pubs[i].append(pub) +# citation_matched_to_pub = False +# for pub in publications: +# if not isinstance(pub, pymed.article.PubMedArticle): +# continue +# all_pubs[i].append(pub) - pub_dict = helper_functions.create_pub_dict_for_saving_PubMed(pub) - pub_id = pub_dict["doi"] if pub_dict["doi"] else pub_dict["pubmed_id"] +# pub_dict = helper_functions.create_pub_dict_for_saving_PubMed(pub) +# pub_id = pub_dict["doi"] if pub_dict["doi"] else pub_dict["pubmed_id"] - ## Match publication to the citation. - if citation["PMID"] == pub_dict["pubmed_id"]: - citation_matched_to_pub = True - elif pub.doi and citation["DOI"] and citation["DOI"].lower() == pub.doi.lower(): - citation_matched_to_pub = True - else: - has_matching_author = helper_functions.match_pub_authors_to_citation_authors(citation["authors"], pub_dict["authors"]) - if has_matching_author and helper_functions.do_strings_fuzzy_match(citation["title"], pub_dict["title"]): - citation_matched_to_pub = True +# ## Match publication to the citation. +# if citation["PMID"] == pub_dict["pubmed_id"]: +# citation_matched_to_pub = True +# elif pub.doi and citation["DOI"] and citation["DOI"].lower() == pub.doi.lower(): +# citation_matched_to_pub = True +# else: +# has_matching_author = helper_functions.match_pub_authors_to_citation_authors(citation["authors"], pub_dict["authors"]) +# if has_matching_author and helper_functions.do_strings_fuzzy_match(citation["title"], pub_dict["title"]): +# citation_matched_to_pub = True - if matching_pub_id := helper_functions.get_pub_id_in_publication_dict(pub_id, pub.title, running_pubs): - if "PubMed" in running_pubs[matching_pub_id]["queried_sources"]: - if not citation_matched_to_pub: - continue - matching_key_for_citation.append(matching_pub_id) - break +# if matching_pub_id := helper_functions.get_pub_id_in_publication_dict(pub_id, pub.title, running_pubs): +# if "PubMed" in running_pubs[matching_pub_id]["queried_sources"]: +# if not citation_matched_to_pub: +# continue +# matching_key_for_citation.append(matching_pub_id) +# break - helper_functions._merge_pub_dicts(running_pubs[matching_pub_id], pub_dict) - running_pubs[matching_pub_id]["queried_sources"].append("PubMed") - if citation_matched_to_pub: - matching_key_for_citation.append(matching_pub_id) - break +# helper_functions._merge_pub_dicts(running_pubs[matching_pub_id], pub_dict) +# running_pubs[matching_pub_id]["queried_sources"].append("PubMed") +# if citation_matched_to_pub: +# matching_key_for_citation.append(matching_pub_id) +# break - else: - if not citation_matched_to_pub: - continue - pub_dict["queried_sources"] = ["PubMed"] - running_pubs[pub_id] = pub_dict - matching_key_for_citation.append(pub_id) - break +# else: +# if not citation_matched_to_pub: +# continue +# pub_dict["queried_sources"] = ["PubMed"] +# running_pubs[pub_id] = pub_dict +# matching_key_for_citation.append(pub_id) +# break - if not citation_matched_to_pub: - matching_key_for_citation.append(None) - time.sleep(1) +# if not citation_matched_to_pub: +# matching_key_for_citation.append(None) +# time.sleep(1) - return running_pubs, matching_key_for_citation, all_pubs +# return running_pubs, matching_key_for_citation, all_pubs - -# def search_references_on_Google_Scholar(tokenized_citations, mailto_email): -# """Searhes Google Scholar for publications that match the citations. - + +# def search_references_on_Crossref(running_pubs, tokenized_citations, mailto_email, prev_query=None): +# """Searhes Crossref for publications matching the citations. + +# For each citation in tokenized_citations Crossref is queried for the publication. +# If the publication is already in running_pubs then missing information will be +# filled in if possible. + # Args: +# running_pubs (dict): dictionary of publications matching the JSON schema for publications. # tokenized_citations (list): list of citations parsed from a source. Each citation is a dict {"authors", "title", "DOI", "PMID", "reference_line", "pub_dict_key"}. -# mailto_email (str): used in the query to Crossref when trying to find DOIs for the articles +# mailto_email (str): used in the query to Crossref. +# prev_query (list|None): a list of lists containing publications from a previous call to this function. [[pub1, ...], [pub1, ...], ...] # Returns: -# publication_dict (dict): keys are pulication ids and values are a dictionary with publication attributes +# running_pubs (dict): keys are pulication ids and values are a dictionary with publication attributes +# matching_key_for_citation (list): list of keys to the publication matching the citation at the same index +# all_pubs (list): list of lists, each index is the pubs searched through after querying until the citation was matched # """ -# publication_dict = {} -# titles = [] +# cr = habanero.Crossref(ua_string = "Academic Tracker (mailto:" + mailto_email + ")") + +# all_pubs = [] # matching_key_for_citation = [] -# for citation in tokenized_citations: +# for i, citation in enumerate(tokenized_citations): +# all_pubs.append([]) -# if citation["title"]: -# query = scholarly.scholarly.search_pubs(citation["title"]) +# if not prev_query: +# if citation["DOI"]: +# results = cr.works(ids = citation["DOI"]) +# works = [results["message"]] +# elif citation["title"]: +# results = cr.works(query_bibliographic = citation["title"], filter = {"type":"journal-article"}, limit = 10) +# works = results["message"]["items"] +# else: +# matching_key_for_citation.append(None) +# continue # else: -# matching_key_for_citation.append(None) -# continue - -# citation_matched = False -# for count, pub in enumerate(query): - -# if count > 50: -# break - -# time.sleep(1) +# works = prev_query[i] + +# citation_matched_to_pub = False +# for work in works: +# all_pubs[i].append(work) -# title = pub["bib"]["title"] +# pub_id, pub_dict = helper_functions.create_pub_dict_for_saving_Crossref(work, prev_query) -# ## authors from Google Scholar are last names and initials in a single string, each string in one list. ['SA Cholewiak', 'RW Fleming', 'M Singh'] -# pub_matched = False -# has_matching_author = any([author_attributes["last"].lower() in author.lower() for author in pub["bib"]["author"] for author_attributes in citation["authors"]]) -# if has_matching_author and fuzzywuzzy.fuzz.ratio(citation["title"], title) >= 90: -# pub_matched = True - -# if not pub_matched: +# if pub_id is None: # continue -# ## Find the publication year and check that it is in range. -# publication_year = int(pub["bib"]["pub_year"]) if "pub_year" in pub["bib"] else None - - -# ## Determine the pub_id -# doi = webio.get_DOI_from_Crossref(title, mailto_email) -# if doi: -# pub_id = DOI_URL + doi +# if citation["DOI"] == pub_dict["doi"]: +# citation_matched_to_pub = True # else: -# if "pub_url" in pub: -# pub_id = pub["pub_url"] -# else: -# helper_functions.vprint("Warning: Could not find a DOI, URL, or PMID for a publication when searching Google Scholar. It will not be in the publications.", verbosity=1) -# helper_functions.vprint("Title: " + title, verbosity=1) +# if "author" in work: +# has_matching_author = helper_functions.match_pub_authors_to_citation_authors(citation["authors"], pub_dict["authors"]) +# if has_matching_author and helper_functions.do_strings_fuzzy_match(citation["title"], pub_dict["title"]): +# citation_matched_to_pub = True + +# ## If the publication is already in running_pubs then try to update missing information. +# if matching_pub_id := helper_functions.get_pub_id_in_publication_dict(pub_id, pub_dict["title"], running_pubs): +# if "Crossref" in running_pubs[matching_pub_id]["queried_sources"]: +# if not citation_matched_to_pub: +# continue +# matching_key_for_citation.append(matching_pub_id) # break - - -# pub_dict = copy.deepcopy(PUBLICATION_TEMPLATE) -# if doi: -# pub_dict["doi"] = doi -# if title: -# pub_dict["title"] = title -# if publication_year: -# pub_dict["publication_date"]["year"] = publication_year +# helper_functions._merge_pub_dicts(running_pubs[matching_pub_id], pub_dict) +# running_pubs[matching_pub_id]["queried_sources"].append("Crossref") +# if citation_matched_to_pub: +# matching_key_for_citation.append(matching_pub_id) +# break -# if not helper_functions.is_pub_in_publication_dict(pub_id, title, publication_dict, titles): -# pub_dict["authors"] = [{"affiliation": None, -# "firstname": None, -# "initials": None, -# "lastname": author["last"]} for author in citation["authors"]] -# publication_dict[pub_id] = pub_dict -# titles.append(title) +# else: +# if not citation_matched_to_pub: +# continue +# pub_dict["queried_sources"] = ["Crossref"] +# running_pubs[pub_id] = pub_dict # matching_key_for_citation.append(pub_id) -# citation_matched = True - -# break - -# if not citation_matched: +# break + +# if not citation_matched_to_pub: # matching_key_for_citation.append(None) +# time.sleep(1) + +# return running_pubs, matching_key_for_citation, all_pubs -# return publication_dict, matching_key_for_citation - -def search_references_on_Crossref(running_pubs, tokenized_citations, mailto_email, prev_query=None): - """Searhes Crossref for publications matching the citations. +def search_references_on_source(source, running_pubs, tokenized_citations, mailto_email, prev_query=None): + """Searhes source for publications matching the citations. - For each citation in tokenized_citations Crossref is queried for the publication. + For each citation in tokenized_citations the source is queried for the publication. If the publication is already in running_pubs then missing information will be filled in if possible. + Possible sources are "Crossref" or "PubMed". + Args: + source (str): must be one of "Crossref" or "PubMed". running_pubs (dict): dictionary of publications matching the JSON schema for publications. tokenized_citations (list): list of citations parsed from a source. Each citation is a dict {"authors", "title", "DOI", "PMID", "reference_line", "pub_dict_key"}. - mailto_email (str): used in the query to Crossref. + mailto_email (str): email provided to the source when querying. prev_query (list|None): a list of lists containing publications from a previous call to this function. [[pub1, ...], [pub1, ...], ...] Returns: @@ -256,54 +258,69 @@ def search_references_on_Crossref(running_pubs, tokenized_citations, mailto_emai matching_key_for_citation (list): list of keys to the publication matching the citation at the same index all_pubs (list): list of lists, each index is the pubs searched through after querying until the citation was matched """ - - cr = habanero.Crossref(ua_string = "Academic Tracker (mailto:" + mailto_email + ")") + + # initiate API + if source == "PubMed": + api = pymed.PubMed(tool=TOOL, email=mailto_email) + query_function = _query_PubMed + skip_pub_function = _pub_needs_skipped_PubMed + pub_dict_creation_function = helper_functions.create_pub_dict_for_saving_PubMed + pub_dict_creation_arguments = ["pub"] + elif source == "Crossref": + api = habanero.Crossref(ua_string = "Academic Tracker (mailto:" + mailto_email + ")") + query_function = _query_Crossref + skip_pub_function = _pub_needs_skipped_Crossref + pub_dict_creation_function = helper_functions.create_pub_dict_for_saving_Crossref + pub_dict_creation_arguments = ["pub", "prev_query"] + else: + helper_functions.vprint("Error: When searching references there was an attempt to query an unknown source, '" + source + "'.") + sys.exit() all_pubs = [] matching_key_for_citation = [] + for i, citation in enumerate(tokenized_citations): all_pubs.append([]) if not prev_query: - if citation["DOI"]: - results = cr.works(ids = citation["DOI"]) - works = [results["message"]] - elif citation["title"]: - results = cr.works(query_bibliographic = citation["title"], filter = {"type":"journal-article"}, limit = 10) - works = results["message"]["items"] - else: + if not (publications := query_function(api, citation)): matching_key_for_citation.append(None) continue else: - works = prev_query[i] - + publications = prev_query[i] + citation_matched_to_pub = False - for work in works: - all_pubs[i].append(work) + for pub in publications: + if skip_pub_function(pub): + continue + all_pubs[i].append(pub) - pub_id, pub_dict = helper_functions.create_pub_dict_for_saving_Crossref(work, prev_query) + locals_ref = locals() + pub_id, pub_dict = pub_dict_creation_function(*[locals_ref[arg] for arg in pub_dict_creation_arguments]) if pub_id is None: continue - if citation["DOI"] == pub_dict["doi"]: + ## Match publication to the citation. + if pub_dict["pubmed_id"] and citation["PMID"] and pub_dict["pubmed_id"] == citation["PMID"]: + citation_matched_to_pub = True + elif pub_dict["doi"] and citation["DOI"] and citation["DOI"].lower() == pub_dict["doi"]: citation_matched_to_pub = True else: - if "author" in work: - has_matching_author = helper_functions.match_pub_authors_to_citation_authors(citation["authors"], pub_dict["authors"]) - if has_matching_author and helper_functions.do_strings_fuzzy_match(citation["title"], pub_dict["title"]): - citation_matched_to_pub = True + has_matching_author = helper_functions.match_pub_authors_to_citation_authors(citation["authors"], pub_dict["authors"]) + if has_matching_author and helper_functions.do_strings_fuzzy_match(citation["title"], pub_dict["title"]): + citation_matched_to_pub = True + - ## If the publication is already in running_pubs then try to update missing information. if matching_pub_id := helper_functions.get_pub_id_in_publication_dict(pub_id, pub_dict["title"], running_pubs): - if "Crossref" in running_pubs[matching_pub_id]["queried_sources"]: + if source in running_pubs[matching_pub_id]["queried_sources"]: if not citation_matched_to_pub: continue matching_key_for_citation.append(matching_pub_id) break helper_functions._merge_pub_dicts(running_pubs[matching_pub_id], pub_dict) - running_pubs[matching_pub_id]["queried_sources"].append("Crossref") + running_pubs[matching_pub_id]["queried_sources"].append(source) if citation_matched_to_pub: matching_key_for_citation.append(matching_pub_id) break @@ -311,18 +328,80 @@ def search_references_on_Crossref(running_pubs, tokenized_citations, mailto_emai else: if not citation_matched_to_pub: continue - pub_dict["queried_sources"] = ["Crossref"] + pub_dict["queried_sources"] = [source] running_pubs[pub_id] = pub_dict matching_key_for_citation.append(pub_id) break - + if not citation_matched_to_pub: matching_key_for_citation.append(None) time.sleep(1) - - return running_pubs, matching_key_for_citation, all_pubs - + return running_pubs, matching_key_for_citation, all_pubs + + + + +def _query_PubMed(pubmed, citation): + """Query PubMed with either the PMID, DOI, or title from citation. + + Args: + pubmed (pymed.api.PubMed): api object from the pymed library. + citation (dict): citation to query for. + """ + + if citation["PMID"]: + query_string = citation["PMID"] + elif citation["DOI"]: + query_string = citation["DOI"] + elif citation["title"]: + query_string = citation["title"] + else: + return None + return pubmed.query(query_string, max_results=10) + + + +def _query_Crossref(cr, citation): + """Query Crossref with either the PMID, DOI, or title from citation. + + Args: + pubmed (habanero.crossref.crossref.Crossref): api object from the habanero library. + citation (dict): citation to query for. + """ + + if citation["DOI"]: + results = cr.works(ids = citation["DOI"]) + works = [results["message"]] + elif citation["title"]: + results = cr.works(query_bibliographic = citation["title"], filter = {"type":"journal-article"}, limit = 10) + works = results["message"]["items"] + else: + return None + return works + + +def _pub_needs_skipped_PubMed(pub): + """Determine whether the queried pub from PubMed should be skipped or not. + + Args: + pub (pymed.article.PubMedArticle|pymed.book.PubMedBookArticle): publication queried from PubMed book articles should be skipped. + """ + + return not isinstance(pub, pymed.article.PubMedArticle) + + +def _pub_needs_skipped_Crossref(pub): + """Determine whether the queried pub from Crossref should be skipped or not. + + This is just here to work with the function, publications from Crossref should never be skipped. + + Args: + pub (dict): publication queried from Crossref. + """ + + return False + diff --git a/src/academic_tracker/tracker_schema.py b/src/academic_tracker/tracker_schema.py index 9ae9f71..472efa9 100644 --- a/src/academic_tracker/tracker_schema.py +++ b/src/academic_tracker/tracker_schema.py @@ -22,7 +22,8 @@ } -config_schema = { +config_schema = \ + { "$schema": "https://json-schema.org/draft/2020-12/schema", "title": "Configuration JSON", "description": "Input file that contains information for how the program should run.", @@ -186,7 +187,7 @@ }, "required": ["project_descriptions", "ORCID_search", "PubMed_search", "Crossref_search", "Authors"] } - +## config_end Marker to denote the end of the schema for documentation. diff --git a/src/academic_tracker/user_input_checking.py b/src/academic_tracker/user_input_checking.py index 94d6b50..fa8ca81 100644 --- a/src/academic_tracker/user_input_checking.py +++ b/src/academic_tracker/user_input_checking.py @@ -52,6 +52,7 @@ def tracker_validate(instance, schema, pattern_messages={}, cls=None, *args, **k message += "The required property " + required_property + " is missing." else: message += "The entry " + "[%s]" % "][".join(repr(index) for index in e.relative_path) + " is missing the required property " + required_property + "." + ## In an older version of JSON Schema the keyword was "dependencies" instead of "dependentRequired". elif e.validator == "dependencies": message += "The entry " + "[%s]" % "][".join(repr(index) for index in e.relative_path) + " is missing a dependent property.\n" message += e.message diff --git a/src/academic_tracker/webio.py b/src/academic_tracker/webio.py index 104e935..3ddc6b5 100644 --- a/src/academic_tracker/webio.py +++ b/src/academic_tracker/webio.py @@ -90,7 +90,6 @@ def search_replace(self, query, method, start, rows, headers, endpoint): if ("ORCID" in author_attributes and author_attributes["ORCID"]) or not "affiliations" in author_attributes: continue - search_results = api.search(author_attributes["pubmed_name_search"], access_token=search_token) for result in search_results["expanded-result"]: @@ -154,7 +153,11 @@ def get_DOI_from_Crossref(title, mailto_email): cr = habanero.Crossref(ua_string = "Academic Tracker (mailto:" + mailto_email + ")") - results = cr.works(query_bibliographic = title, filter = {"type":"journal-article"}) + try: + results = cr.works(query_bibliographic = title, filter = {"type":"journal-article"}) + except: + helper_functions.vprint("Warning: There was an error querying Crossref to get the DOI for the publication titled: " + title) + return None for work in results["message"]["items"]: @@ -266,150 +269,150 @@ def send_emails(email_messages): ## Unused Functions ############### -def get_grants_from_Crossref(title, mailto_email, grants): - """Search title on Crossref and try to find the grants associated with it. +# def get_grants_from_Crossref(title, mailto_email, grants): +# """Search title on Crossref and try to find the grants associated with it. - Only the grants in the grants parameter are searched for because trying to find - all grants associated with the article is too difficult. +# Only the grants in the grants parameter are searched for because trying to find +# all grants associated with the article is too difficult. - Args: - title (str): string of the title of the journal article to search for. - mailto_email (str): an email address needed to search Crossref more effectively. - grants (list): a list of the grants to try and find for the article. +# Args: +# title (str): string of the title of the journal article to search for. +# mailto_email (str): an email address needed to search Crossref more effectively. +# grants (list): a list of the grants to try and find for the article. - Returns: - found_grants (str): Either None or a list of grants found for the article. - """ +# Returns: +# found_grants (str): Either None or a list of grants found for the article. +# """ - found_grants = None +# found_grants = None - cr = habanero.Crossref(ua_string = "Academic Tracker (mailto:" + mailto_email + ")") +# cr = habanero.Crossref(ua_string = "Academic Tracker (mailto:" + mailto_email + ")") - results = cr.works(query_bibliographic = title, filter = {"type":"journal-article"}) +# results = cr.works(query_bibliographic = title, filter = {"type":"journal-article"}) - for work in results["message"]["items"]: +# for work in results["message"]["items"]: - if not "title" in work or not helper_functions.is_fuzzy_match_to_list(title, work["title"]): - continue +# if not "title" in work or not helper_functions.is_fuzzy_match_to_list(title, work["title"]): +# continue - if "funder" in work: - ## the grant string could be in any value of the funder dict so look for it in each one. - found_grants = {grant for funder in work["funder"] for value in funder.values() for grant in grants if grant in value} - if found_grants: - found_grants = list(found_grants) +# if "funder" in work: +# ## the grant string could be in any value of the funder dict so look for it in each one. +# found_grants = {grant for funder in work["funder"] for value in funder.values() for grant in grants if grant in value} +# if found_grants: +# found_grants = list(found_grants) - ## Crossref should only have one result that matches the title, so if it got past the check at the top break. - break +# ## Crossref should only have one result that matches the title, so if it got past the check at the top break. +# break - return found_grants +# return found_grants -def get_redirect_url_from_doi(doi): - """""" +# def get_redirect_url_from_doi(doi): +# """""" - doi = doi.lower() +# doi = doi.lower() - if re.match(r".*http.*", doi): - match = helper_functions.regex_match_return(r".*doi.org/(.*)", doi) - if match: - url = DOI_URL + "api/handles/" + match[0] - else: - return "" - else: - url = DOI_URL + "api/handles/" + doi +# if re.match(r".*http.*", doi): +# match = helper_functions.regex_match_return(r".*doi.org/(.*)", doi) +# if match: +# url = DOI_URL + "api/handles/" + match[0] +# else: +# return "" +# else: +# url = DOI_URL + "api/handles/" + doi - try: - req = urllib.request.Request(url) - response = urllib.request.urlopen(req) - json_response = json.loads(response.read()) - response.close() +# try: +# req = urllib.request.Request(url) +# response = urllib.request.urlopen(req) +# json_response = json.loads(response.read()) +# response.close() - except urllib.error.HTTPError: - helper_functions.vprint("Error trying to resolve DOI: " + doi, verbosity=1) - return "" +# except urllib.error.HTTPError: +# helper_functions.vprint("Error trying to resolve DOI: " + doi, verbosity=1) +# return "" - for value in json_response["values"]: - if value["type"] == "URL": - return value["data"]["value"] +# for value in json_response["values"]: +# if value["type"] == "URL": +# return value["data"]["value"] - return "" +# return "" -def scrape_url_for_DOI(url): - """Searches url for DOI. +# def scrape_url_for_DOI(url): +# """Searches url for DOI. - Uses the regex "(?i).*doi:\s*([^\s]+\w).*" to look for a DOI on - the provided url. The DOI is visited to confirm it is a proper DOI. +# Uses the regex "(?i).*doi:\s*([^\s]+\w).*" to look for a DOI on +# the provided url. The DOI is visited to confirm it is a proper DOI. - Args: - url (str): url to search. +# Args: +# url (str): url to search. - Returns: - DOI (str): string of the DOI found on the webpage. Is empty string if DOI is not found. - """ +# Returns: +# DOI (str): string of the DOI found on the webpage. Is empty string if DOI is not found. +# """ - url_str = get_url_contents_as_str(url) - if not url_str: - return "" +# url_str = get_url_contents_as_str(url) +# if not url_str: +# return "" - doi = helper_functions.regex_group_return(helper_functions.regex_search_return(r"(?i)doi:\s*(<[^>]*>)?([^\s<]+)", url_str), 1) +# doi = helper_functions.regex_group_return(helper_functions.regex_search_return(r"(?i)doi:\s*(<[^>]*>)?([^\s<]+)", url_str), 1) - if doi: +# if doi: - url = get_redirect_url_from_doi(doi) - return doi if url else "" +# url = get_redirect_url_from_doi(doi) +# return doi if url else "" - else: - return "" +# else: +# return "" -def check_doi_for_grants(doi, grants): - """Searches DOI webpage for grants. +# def check_doi_for_grants(doi, grants): +# """Searches DOI webpage for grants. - Concatenates "https://doi.org/" with the doi, visits the - page and looks for the given grants on that page. +# Concatenates "https://doi.org/" with the doi, visits the +# page and looks for the given grants on that page. - Args: - doi (str): DOI for the publication. - grants (list): list of str for each grant to look for. +# Args: +# doi (str): DOI for the publication. +# grants (list): list of str for each grant to look for. - Returns: - found_grants (list): list of str with each grant that was found on the page. - """ +# Returns: +# found_grants (list): list of str with each grant that was found on the page. +# """ - url = get_redirect_url_from_doi(doi) - if not url: - return set() +# url = get_redirect_url_from_doi(doi) +# if not url: +# return set() - url_str = get_url_contents_as_str(url) - if not url_str: - return set() +# url_str = get_url_contents_as_str(url) +# if not url_str: +# return set() - return { grant for grant in grants if grant in url_str } +# return { grant for grant in grants if grant in url_str } -def download_pdf(pdf_url): - """ - """ - ## test url https://realpython.com/python-tricks-sample-pdf - try: - req = urllib.request.Request(pdf_url, headers={"User-Agent": "Mozilla/5.0"}) - response = urllib.request.urlopen(req) - pdf_bytes = io.BytesIO(response.read()) - response.close() +# def download_pdf(pdf_url): +# """ +# """ +# ## test url https://realpython.com/python-tricks-sample-pdf +# try: +# req = urllib.request.Request(pdf_url, headers={"User-Agent": "Mozilla/5.0"}) +# response = urllib.request.urlopen(req) +# pdf_bytes = io.BytesIO(response.read()) +# response.close() - except urllib.error.HTTPError as e: - helper_functions.vprint(e, verbosity=1) - helper_functions.vprint(pdf_url, verbosity=1) +# except urllib.error.HTTPError as e: +# helper_functions.vprint(e, verbosity=1) +# helper_functions.vprint(pdf_url, verbosity=1) - return None +# return None - return pdf_bytes +# return pdf_bytes \ No newline at end of file diff --git a/tests/fixtures.py b/tests/fixtures.py index e6cf166..d4189bb 100644 --- a/tests/fixtures.py +++ b/tests/fixtures.py @@ -6,6 +6,9 @@ import pymed from academic_tracker.helper_functions import create_pub_dict_for_saving_PubMed from academic_tracker.fileio import load_json +from academic_tracker import webio + +DOI_URL = webio.DOI_URL @pytest.fixture @@ -46,11 +49,11 @@ def pub_with_grants(): def publication_dict(pub_with_grants, pub_with_matching_author): publication_dict = {} - pub_dict = create_pub_dict_for_saving_PubMed(pub_with_grants) - publication_dict[pub_dict["doi"]] = pub_dict + _, pub_dict = create_pub_dict_for_saving_PubMed(pub_with_grants) + publication_dict[DOI_URL + pub_dict["doi"]] = pub_dict - pub_dict = create_pub_dict_for_saving_PubMed(pub_with_matching_author) - publication_dict[pub_dict["doi"]] = pub_dict + _, pub_dict = create_pub_dict_for_saving_PubMed(pub_with_matching_author) + publication_dict[DOI_URL + pub_dict["doi"]] = pub_dict return publication_dict diff --git a/tests/regen_intermediate_files_ref.py b/tests/regen_intermediate_files_ref.py index c47b5e8..09e72fb 100644 --- a/tests/regen_intermediate_files_ref.py +++ b/tests/regen_intermediate_files_ref.py @@ -9,35 +9,44 @@ import pymed import xml.etree.ElementTree as ET +import pytest from academic_tracker.fileio import load_json -from academic_tracker.ref_srch_webio import search_references_on_PubMed, search_references_on_Crossref +from academic_tracker.ref_srch_webio import search_references_on_source from academic_tracker.ref_srch_modularized import build_publication_dict -config_dict_Hunter_only = load_json(os.path.join("tests", "testing_files", "config_Hunter_only.json")) -tokenized_citations = load_json(os.path.join("tests", "testing_files", "tokenized_ref_test.json")) +@pytest.fixture +def config_dict_Hunter_only(): + return load_json(os.path.join("tests", "testing_files", "config_Hunter_only.json")) -original_queries = load_json(os.path.join("tests", "testing_files", "all_queries_ref.json")) -## Convert PubMed dictionaries back to articles class. -for i, pub_list in enumerate(original_queries["PubMed"]): - new_list = [] - for pub in pub_list: - new_list.append(pymed.article.PubMedArticle(ET.fromstring(pub["xml"]))) - original_queries["PubMed"][i] = new_list +@pytest.fixture +def tokenized_citations(): + return load_json(os.path.join("tests", "testing_files", "tokenized_ref_test.json")) +@pytest.fixture +def original_queries(): + query_json = load_json(os.path.join("tests", "testing_files", "all_queries_ref.json")) + ## Convert PubMed dictionaries back to articles class. + for i, pub_list in enumerate(query_json["PubMed"]): + new_list = [] + for pub in pub_list: + new_list.append(pymed.article.PubMedArticle(ET.fromstring(pub["xml"]))) + query_json["PubMed"][i] = new_list + return query_json -def test_build_publication_dict_with_Crossref(mocker): + +def test_build_publication_dict_with_Crossref(mocker, config_dict_Hunter_only, original_queries, tokenized_citations): running_pubs = {} - running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_PubMed(running_pubs, tokenized_citations, "asdf", original_queries["PubMed"]) - running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_Crossref(copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["Crossref"]) + running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_source("PubMed", running_pubs, tokenized_citations, "asdf", original_queries["PubMed"]) + running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_source("Crossref", copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["Crossref"]) - running_pubs3, matching_key_for_citation3, all_pubs = search_references_on_PubMed(copy.deepcopy(running_pubs2), tokenized_citations, "asdf", original_queries["PubMed"]) - running_pubs4, matching_key_for_citation4, all_pubs = search_references_on_Crossref(copy.deepcopy(running_pubs3), tokenized_citations, "asdf", original_queries["Crossref"]) + running_pubs3, matching_key_for_citation3, all_pubs = search_references_on_source("PubMed", copy.deepcopy(running_pubs2), tokenized_citations, "asdf", original_queries["PubMed"]) + running_pubs4, matching_key_for_citation4, all_pubs = search_references_on_source("Crossref", copy.deepcopy(running_pubs3), tokenized_citations, "asdf", original_queries["Crossref"]) with open(os.path.join("tests", "testing_files", "new_intermediate_results", "ref_search", "all", "running_pubs1.json"),'w') as jsonFile: @@ -59,14 +68,11 @@ def test_build_publication_dict_with_Crossref(mocker): jsonFile.write(json.dumps(matching_key_for_citation4, indent=2, sort_keys=True)) - mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_PubMed", + mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_source", side_effect=[(running_pubs1, matching_key_for_citation1, original_queries["PubMed"]), - (running_pubs3, matching_key_for_citation3, original_queries["PubMed"])]) - - mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_Crossref", - side_effect=[(running_pubs2, matching_key_for_citation2, original_queries["Crossref"]), - (running_pubs4, matching_key_for_citation4, original_queries["Crossref"])]) - + (running_pubs2, matching_key_for_citation2, original_queries["Crossref"]), + (running_pubs3, matching_key_for_citation3, original_queries["PubMed"]), + (running_pubs4, matching_key_for_citation4, original_queries["Crossref"])]) actual_publication_dict, actual_tokenized_citations, _ = build_publication_dict(config_dict_Hunter_only, tokenized_citations, False, False) @@ -79,12 +85,12 @@ def test_build_publication_dict_with_Crossref(mocker): -def test_build_publication_dict_no_Crossref(mocker): +def test_build_publication_dict_no_Crossref(mocker, config_dict_Hunter_only, original_queries, tokenized_citations): running_pubs = {} - running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_PubMed(running_pubs, tokenized_citations, "asdf", original_queries["PubMed"]) + running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_source("PubMed", running_pubs, tokenized_citations, "asdf", original_queries["PubMed"]) - running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_PubMed(copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["PubMed"]) + running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_source("PubMed", copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["PubMed"]) with open(os.path.join("tests", "testing_files", "new_intermediate_results", "ref_search", "no_Crossref", "running_pubs1.json"),'w') as jsonFile: @@ -98,7 +104,7 @@ def test_build_publication_dict_no_Crossref(mocker): jsonFile.write(json.dumps(matching_key_for_citation2, indent=2, sort_keys=True)) - mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_PubMed", + mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_source", side_effect=[(running_pubs1, matching_key_for_citation1, original_queries["PubMed"]), (running_pubs2, matching_key_for_citation2, original_queries["PubMed"])]) @@ -115,12 +121,12 @@ def test_build_publication_dict_no_Crossref(mocker): -def test_build_publication_dict_no_PubMed(mocker): +def test_build_publication_dict_no_PubMed(mocker, config_dict_Hunter_only, original_queries, tokenized_citations): running_pubs = {} - running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_Crossref(running_pubs, tokenized_citations, "asdf", original_queries["Crossref"]) + running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_source("Crossref", running_pubs, tokenized_citations, "asdf", original_queries["Crossref"]) - running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_Crossref(copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["Crossref"]) + running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_source("Crossref", copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["Crossref"]) with open(os.path.join("tests", "testing_files", "new_intermediate_results", "ref_search", "no_PubMed", "running_pubs1.json"),'w') as jsonFile: @@ -134,7 +140,7 @@ def test_build_publication_dict_no_PubMed(mocker): jsonFile.write(json.dumps(matching_key_for_citation2, indent=2, sort_keys=True)) - mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_Crossref", + mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_source", side_effect=[(running_pubs1, matching_key_for_citation1, original_queries["Crossref"]), (running_pubs2, matching_key_for_citation2, original_queries["Crossref"])]) diff --git a/tests/test_athr_srch_emails_and_reports.py b/tests/test_athr_srch_emails_and_reports.py index 933a964..0de3415 100644 --- a/tests/test_athr_srch_emails_and_reports.py +++ b/tests/test_athr_srch_emails_and_reports.py @@ -88,6 +88,8 @@ def authors_by_project_dict_tabular(): def test_create_project_reports_and_emails_tabular(publication_dict, config_dict_tabular, authors_by_project_dict_tabular): + ## Add a filename to a project report to test that it will create it correctly. + authors_by_project_dict_tabular["Core A Administrative Core"]["Hunter Moseley"]["project_report"]["filename"] = "asdf.csv" ## Add Travis to a publication so we can test that multiple authors are sent emails. publication_dict["https://doi.org/10.1038/s41597-023-02277-x"]["authors"][1]["author_id"] = "Travis Thompson" @@ -108,6 +110,7 @@ def test_create_project_reports_and_emails_tabular(publication_dict, config_dict number_of_excel_files = len([name for name in dir_contents if ".xlsx" in name]) + assert "asdf.csv" in dir_contents assert expected_emails == actual_emails assert number_of_excel_files == 1 assert "no_from_email_report.csv" in dir_contents diff --git a/tests/test_athr_srch_webio_no_internet.py b/tests/test_athr_srch_webio_no_internet.py index c70c0c0..6e53cb0 100644 --- a/tests/test_athr_srch_webio_no_internet.py +++ b/tests/test_athr_srch_webio_no_internet.py @@ -231,14 +231,6 @@ def test_search_Google_Scholar_for_pubs_query_error(config_dict_Hunter_only, ori assert ("Warning: The \"scholar_id\" for author Hunter Moseley is probably " "incorrect, an error occured when trying to query Google Scholar.\n") in captured.out assert r'Traceback (most recent call last):' in captured.out - assert r' File "C:\Python310\lib\site-packages\academic_tracker\athr_srch_webio.py", line 296, in search_Google_Scholar_for_pubs' in captured.out - assert r' queried_author = scholarly.scholarly.search_author_id(authors_attributes["scholar_id"])' in captured.out - assert r' File "C:\Python310\lib\unittest\mock.py", line 1104, in __call__' in captured.out - assert r' return self._mock_call(*args, **kwargs)' in captured.out - assert r' File "C:\Python310\lib\unittest\mock.py", line 1108, in _mock_call' in captured.out - assert r' return self._execute_mock_call(*args, **kwargs)' in captured.out - assert r' File "C:\Python310\lib\unittest\mock.py", line 1167, in _execute_mock_call' in captured.out - assert r' raise result' in captured.out assert r'Exception' in captured.out diff --git a/tests/test_citation_parsing.py b/tests/test_citation_parsing.py index f911ea4..98c9042 100644 --- a/tests/test_citation_parsing.py +++ b/tests/test_citation_parsing.py @@ -71,6 +71,7 @@ def test_tokenize_MLA_or_Chicago_authors(authors_string, authors): @pytest.mark.parametrize("authors_string, authors", [ ("last_name, A.B.", [{"last":"last_name", "initials":"A.B."}]), + (", A.B.", [{"last":"", "initials":"A.B."}]), ("last_name, A.B. et al.", [{"last":"last_name", "initials":"A.B."}]), ("last_name1, A.B., last_name2, C.D.", [{"last":"last_name1", "initials":"A.B."}, {"last":"last_name2", "initials":"C.D."}]), diff --git a/tests/test_emails_and_reports_helpers.py b/tests/test_emails_and_reports_helpers.py index bb59556..1e97d86 100644 --- a/tests/test_emails_and_reports_helpers.py +++ b/tests/test_emails_and_reports_helpers.py @@ -97,8 +97,8 @@ def test_replace_keywords1(publication_dict, config_dict, tokenized_citations): 'Title': 'Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases', 'PMCID': 'None', 'Publication Year': '2020', - 'Publication Month': 'None', - 'Publication Day': 'None', + 'Publication Month': '9', + 'Publication Day': '11', 'Tok Title': 'Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.', 'Tok DOI': '10.3390/metabo10090368', 'Tok PMID': 'None', @@ -143,8 +143,8 @@ def test_replace_keywords2(publication_dict, config_dict, tokenized_citations): 'Title': 'Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases', 'PMCID': 'None', 'Publication Year': '2020', - 'Publication Month': 'None', - 'Publication Day': 'None', + 'Publication Month': '9', + 'Publication Day': '11', 'Tok Title': 'Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.', 'Tok DOI': '10.3390/metabo10090368', 'Tok PMID': 'None', diff --git a/tests/test_helper_functions.py b/tests/test_helper_functions.py index bedce03..2a4fd53 100644 --- a/tests/test_helper_functions.py +++ b/tests/test_helper_functions.py @@ -19,272 +19,272 @@ -# def test_vprint(capsys): +def test_vprint(capsys): -# vprint("asdf") -# captured = capsys.readouterr() + vprint("asdf") + captured = capsys.readouterr() -# assert captured.out == "asdf\n" + assert captured.out == "asdf\n" -# def test_vprint_silent(monkeypatch, capsys): -# monkeypatch.setattr(__main__, "SILENT", True) +def test_vprint_silent(monkeypatch, capsys): + monkeypatch.setattr(__main__, "SILENT", True) -# vprint("asdf") -# captured = capsys.readouterr() + vprint("asdf") + captured = capsys.readouterr() -# assert captured.out == "" + assert captured.out == "" -# def test_vprint_verbose_on(capsys): +def test_vprint_verbose_on(capsys): -# vprint("asdf", verbosity=1) -# captured = capsys.readouterr() + vprint("asdf", verbosity=1) + captured = capsys.readouterr() -# assert captured.out == "asdf\n" + assert captured.out == "asdf\n" -# def test_vprint_verbose_off(monkeypatch, capsys): -# monkeypatch.setattr(__main__, "VERBOSE", False) +def test_vprint_verbose_off(monkeypatch, capsys): + monkeypatch.setattr(__main__, "VERBOSE", False) -# vprint("asdf", verbosity=1) -# captured = capsys.readouterr() + vprint("asdf", verbosity=1) + captured = capsys.readouterr() -# assert captured.out == "" + assert captured.out == "" -# @pytest.mark.parametrize("regex, string_to_match, return_value", [ +@pytest.mark.parametrize("regex, string_to_match, return_value", [ -# (r"(?i).*doi:\s*([^\s]+\w).*", "asdfasdfasdf", ()), -# (r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf", re.match(r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf").groups()), -# ]) + (r"(?i).*doi:\s*([^\s]+\w).*", "asdfasdfasdf", ()), + (r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf", re.match(r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf").groups()), + ]) -# def test_regex_match_return(regex, string_to_match, return_value): +def test_regex_match_return(regex, string_to_match, return_value): -# assert regex_match_return(regex, string_to_match) == return_value + assert regex_match_return(regex, string_to_match) == return_value -# @pytest.mark.parametrize("regex_group, index, return_value", [ +@pytest.mark.parametrize("regex_group, index, return_value", [ -# (re.match(r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf").groups(), 0, "asdf"), -# ((), 0, ""), -# (re.match(r"(a*)(b*)", "aaaaabb").groups(), 1, "bb") -# ]) + (re.match(r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf").groups(), 0, "asdf"), + ((), 0, ""), + (re.match(r"(a*)(b*)", "aaaaabb").groups(), 1, "bb") + ]) -# def test_regex_group_return(regex_group, index, return_value): +def test_regex_group_return(regex_group, index, return_value): -# assert regex_group_return(regex_group, index) == return_value + assert regex_group_return(regex_group, index) == return_value -# @pytest.mark.parametrize("regex, string_to_match, return_value", [ +@pytest.mark.parametrize("regex, string_to_match, return_value", [ -# (r"(?i).*doi:\s*([^\s]+\w).*", "asdfasdfasdf", ()), -# (r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf", re.search(r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf").groups()), -# ]) - -# def test_regex_search_return(regex, string_to_match, return_value): - -# assert regex_search_return(regex, string_to_match) == return_value - - - -# @pytest.fixture -# def authors_json_file(): -# return { -# "Isabel Escobar": { -# "ORCID": "0000-0001-9269-5927", -# "affiliations": [ -# "kentucky" -# ], -# "cutoff_year": 2020, -# "email": "isabel.escobar@uky.edu", -# "first_name": "Isabel", -# "last_name": "Escobar", -# "pubmed_name_search": "Isabel Escobar", -# "scholar_id": "RfB5L8kAAAAJ" -# }, -# "Hunter Moseley": { -# "ORCID": "0000-0003-3995-5368", -# "affiliations": [ -# "kentucky" -# ], -# "cutoff_year": 2020, -# "email": "hunter.moseley@gmail.com", -# "first_name": "Hunter", -# "last_name": "Moseley", -# "pubmed_name_search": "Hunter Moseley", -# "scholar_id": "ctE_FZMAAAAJ" -# }} - - -# @pytest.mark.parametrize("PM_author_list, returned_PM_author_list", [ + (r"(?i).*doi:\s*([^\s]+\w).*", "asdfasdfasdf", ()), + (r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf", re.search(r"(?i).*doi:\s*([^\s]+\w).*", "doi: asdf").groups()), + ]) + +def test_regex_search_return(regex, string_to_match, return_value): + + assert regex_search_return(regex, string_to_match) == return_value + + + +@pytest.fixture +def authors_json_file(): + return { + "Isabel Escobar": { + "ORCID": "0000-0001-9269-5927", + "affiliations": [ + "kentucky" + ], + "cutoff_year": 2020, + "email": "isabel.escobar@uky.edu", + "first_name": "Isabel", + "last_name": "Escobar", + "pubmed_name_search": "Isabel Escobar", + "scholar_id": "RfB5L8kAAAAJ" + }, + "Hunter Moseley": { + "ORCID": "0000-0003-3995-5368", + "affiliations": [ + "kentucky" + ], + "cutoff_year": 2020, + "email": "hunter.moseley@gmail.com", + "first_name": "Hunter", + "last_name": "Moseley", + "pubmed_name_search": "Hunter Moseley", + "scholar_id": "ctE_FZMAAAAJ" + }} + + +@pytest.mark.parametrize("PM_author_list, returned_PM_author_list", [ -# ([{ 'affiliation': 'Department of Neurology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany.', -# 'firstname': 'Carine', -# 'initials': 'C', -# 'lastname': 'Thalman', -# 'ORCID':None}, -# { 'affiliation': 'Department of Biostats, Kentucky', -# 'firstname': 'Hunter', -# 'initials': 'HM', -# 'lastname': 'Moseley', -# 'ORCID':None},], -# [{ 'affiliation': 'Department of Neurology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany.', -# 'firstname': 'Carine', -# 'initials': 'C', -# 'lastname': 'Thalman', -# 'ORCID':None}, -# { 'affiliation': 'Department of Biostats, Kentucky', -# 'firstname': 'Hunter', -# 'initials': 'HM', -# 'lastname': 'Moseley', -# 'author_id': 'Hunter Moseley', -# 'ORCID':"0000-0003-3995-5368"},]), + ([{ 'affiliation': 'Department of Neurology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany.', + 'firstname': 'Carine', + 'initials': 'C', + 'lastname': 'Thalman', + 'ORCID':None}, + { 'affiliation': 'Department of Biostats, Kentucky', + 'firstname': 'Hunter', + 'initials': 'HM', + 'lastname': 'Moseley', + 'ORCID':None},], + [{ 'affiliation': 'Department of Neurology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany.', + 'firstname': 'Carine', + 'initials': 'C', + 'lastname': 'Thalman', + 'ORCID':None}, + { 'affiliation': 'Department of Biostats, Kentucky', + 'firstname': 'Hunter', + 'initials': 'HM', + 'lastname': 'Moseley', + 'author_id': 'Hunter Moseley', + 'ORCID':"0000-0003-3995-5368"},]), -# ([{ 'affiliation': 'Department of Neurology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany.', -# 'firstname': 'Carine', -# 'initials': 'C', -# 'lastname': 'Thalman', -# 'ORCID':None}], -# []), + ([{ 'affiliation': 'Department of Neurology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany.', + 'firstname': 'Carine', + 'initials': 'C', + 'lastname': 'Thalman', + 'ORCID':None}], + []), -# ([{ 'affiliation': 'Department of Biostats, Kentucky', -# 'firstname': 'Hunter N. B.', -# 'initials': 'HM', -# 'lastname': 'Moseley', -# 'ORCID':None},], -# [{ 'affiliation': 'Department of Biostats, Kentucky', -# 'firstname': 'Hunter N. B.', -# 'initials': 'HM', -# 'lastname': 'Moseley', -# 'author_id': 'Hunter Moseley', -# 'ORCID':"0000-0003-3995-5368"},]), + ([{ 'affiliation': 'Department of Biostats, Kentucky', + 'firstname': 'Hunter N. B.', + 'initials': 'HM', + 'lastname': 'Moseley', + 'ORCID':None},], + [{ 'affiliation': 'Department of Biostats, Kentucky', + 'firstname': 'Hunter N. B.', + 'initials': 'HM', + 'lastname': 'Moseley', + 'author_id': 'Hunter Moseley', + 'ORCID':"0000-0003-3995-5368"},]), -# ([{ 'affiliation': 'Department of Biostats, Kentucky', -# 'firstname': 'X Hunter', -# 'initials': 'HM', -# 'lastname': 'Moseley', -# 'ORCID':None},], -# [{ 'affiliation': 'Department of Biostats, Kentucky', -# 'firstname': 'X Hunter', -# 'initials': 'HM', -# 'lastname': 'Moseley', -# 'author_id': 'Hunter Moseley', -# 'ORCID':"0000-0003-3995-5368"},]), + ([{ 'affiliation': 'Department of Biostats, Kentucky', + 'firstname': 'X Hunter', + 'initials': 'HM', + 'lastname': 'Moseley', + 'ORCID':None},], + [{ 'affiliation': 'Department of Biostats, Kentucky', + 'firstname': 'X Hunter', + 'initials': 'HM', + 'lastname': 'Moseley', + 'author_id': 'Hunter Moseley', + 'ORCID':"0000-0003-3995-5368"},]), -# ([{ 'collectivename': 'some name', -# 'ORCID':None},], -# [{ 'collectivename': 'some name', -# 'author_id': 'Hunter Moseley', -# 'ORCID':"0000-0003-3995-5368"},]), + ([{ 'collectivename': 'some name', + 'ORCID':None},], + [{ 'collectivename': 'some name', + 'author_id': 'Hunter Moseley', + 'ORCID':"0000-0003-3995-5368"},]), -# ([{ 'affiliation': 'Department of Biostats, Kentucky', -# 'firstname': 'Hunter N. B.', -# 'initials': 'HM', -# 'lastname': None, -# 'ORCID':None},], -# []), -# ]) + ([{ 'affiliation': 'Department of Biostats, Kentucky', + 'firstname': 'Hunter N. B.', + 'initials': 'HM', + 'lastname': None, + 'ORCID':None},], + []), + ]) -# def test_match_pub_authors_to_config_authors(authors_json_file, PM_author_list, returned_PM_author_list): -# if "collectivename" in PM_author_list[0]: -# authors_json_file["Hunter Moseley"]["collective_name"] = "some name" - -# assert match_pub_authors_to_config_authors(authors_json_file, PM_author_list) == returned_PM_author_list - - - -# def test_match_authors_in_pub_PubMed_collective_names(): - -# citation_authors = [ -# { -# "initials": "J", -# "last": "Mitchell" -# }, -# {"collective_name": "some name"}, -# { -# "initials": "R", -# "last": "Flight" -# }, -# { -# "initials": "H", -# "last": "Moseley" -# } -# ] - -# publication_authors = [ -# {"collectivename": "some name", -# "ORCID": None} -# ] - -# assert match_pub_authors_to_citation_authors(citation_authors, publication_authors) == True - - -# def test_match_authors_in_pub_PubMed_ORCID(): - -# citation_authors = [ -# { -# "initials": "J", -# "last": "Mitchell" -# }, -# {"ORCID": "asdf"}, -# { -# "initials": "R", -# "last": "Flight" -# }, -# { -# "initials": "H", -# "last": "Moseley" -# } -# ] - -# publication_authors = [ -# {"ORCID": "asdf", -# "lastname": "qwer"} -# ] - -# assert match_pub_authors_to_citation_authors(citation_authors, publication_authors) == True - - -# @pytest.fixture -# def pub_no_PMCID(): -# xml_path = os.path.join("tests", "testing_files", "no_author.xml") -# tree = ET.parse(xml_path) -# return pymed.article.PubMedArticle(xml_element=tree.getroot()) - - -# def test_modify_pub_dict_for_saving_no_PMCID(pub_no_PMCID): -# modified_pub = load_json(os.path.join("tests", "testing_files", "PubMed_modified_to_save_no_PMCID.json")) +def test_match_pub_authors_to_config_authors(authors_json_file, PM_author_list, returned_PM_author_list): + if "collectivename" in PM_author_list[0]: + authors_json_file["Hunter Moseley"]["collective_name"] = "some name" + + assert match_pub_authors_to_config_authors(authors_json_file, PM_author_list) == returned_PM_author_list + + + +def test_match_authors_in_pub_PubMed_collective_names(): + + citation_authors = [ + { + "initials": "J", + "last": "Mitchell" + }, + {"collective_name": "some name"}, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "H", + "last": "Moseley" + } + ] + + publication_authors = [ + {"collectivename": "some name", + "ORCID": None} + ] + + assert match_pub_authors_to_citation_authors(citation_authors, publication_authors) == True + + +def test_match_authors_in_pub_PubMed_ORCID(): + + citation_authors = [ + { + "initials": "J", + "last": "Mitchell" + }, + {"ORCID": "asdf"}, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "H", + "last": "Moseley" + } + ] + + publication_authors = [ + {"ORCID": "asdf", + "lastname": "qwer"} + ] + + assert match_pub_authors_to_citation_authors(citation_authors, publication_authors) == True + + +@pytest.fixture +def pub_no_PMCID(): + xml_path = os.path.join("tests", "testing_files", "no_author.xml") + tree = ET.parse(xml_path) + return pymed.article.PubMedArticle(xml_element=tree.getroot()) + + +def test_modify_pub_dict_for_saving_no_PMCID(pub_no_PMCID): + modified_pub = load_json(os.path.join("tests", "testing_files", "PubMed_modified_to_save_no_PMCID.json")) -# pub_to_check = create_pub_dict_for_saving_PubMed(pub_no_PMCID) + _, pub_to_check = create_pub_dict_for_saving_PubMed(pub_no_PMCID) -# # with open(os.path.join("tests", "testing_files", "PubMed_modified_to_save_no_PMCID_new.json"),'w') as jsonFile: -# # jsonFile.write(json.dumps(pub_to_check, indent=2, sort_keys=True)) + # with open(os.path.join("tests", "testing_files", "PubMed_modified_to_save_no_PMCID_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(pub_to_check, indent=2, sort_keys=True)) -# assert pub_to_check == modified_pub + assert pub_to_check == modified_pub -# @pytest.fixture -# def pub_with_PMCID(): -# xml_path = os.path.join("tests", "testing_files", "pub_with_PMCID.xml") -# tree = ET.parse(xml_path) -# return pymed.article.PubMedArticle(xml_element=tree.getroot()) +@pytest.fixture +def pub_with_PMCID(): + xml_path = os.path.join("tests", "testing_files", "pub_with_PMCID.xml") + tree = ET.parse(xml_path) + return pymed.article.PubMedArticle(xml_element=tree.getroot()) -# def test_modify_pub_dict_for_saving_with_PMCID(pub_with_PMCID): -# modified_pub = load_json(os.path.join("tests", "testing_files", "PubMed_modified_to_save_with_PMCID.json")) +def test_modify_pub_dict_for_saving_with_PMCID(pub_with_PMCID): + modified_pub = load_json(os.path.join("tests", "testing_files", "PubMed_modified_to_save_with_PMCID.json")) -# pub_to_check = create_pub_dict_for_saving_PubMed(pub_with_PMCID, True) + _, pub_to_check = create_pub_dict_for_saving_PubMed(pub_with_PMCID, True) -# # with open(os.path.join("tests", "testing_files", "PubMed_modified_to_save_with_PMCID_new.json"),'w') as jsonFile: -# # jsonFile.write(json.dumps(pub_to_check, indent=2, sort_keys=True)) + # with open(os.path.join("tests", "testing_files", "PubMed_modified_to_save_with_PMCID_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(pub_to_check, indent=2, sort_keys=True)) -# assert pub_to_check == modified_pub + assert pub_to_check == modified_pub @@ -298,7 +298,7 @@ def modified_PubMed_XML(): def test_modify_pub_dict_for_saving_with_PMCID(modified_PubMed_XML): modified_pub = load_json(os.path.join("tests", "testing_files", "PubMed_rare_cases.json")) - pub_to_check = create_pub_dict_for_saving_PubMed(modified_PubMed_XML, True) + _, pub_to_check = create_pub_dict_for_saving_PubMed(modified_PubMed_XML, True) # with open(os.path.join("tests", "testing_files", "PubMed_rare_cases_new.json"),'w') as jsonFile: # jsonFile.write(json.dumps(pub_to_check, indent=2, sort_keys=True)) @@ -307,131 +307,131 @@ def test_modify_pub_dict_for_saving_with_PMCID(modified_PubMed_XML): -# @pytest.mark.parametrize("str_to_match, list_to_matched, is_match", [ +@pytest.mark.parametrize("str_to_match, list_to_matched, is_match", [ -# ("asdf", ["qwer", "asdf", "zxcv"], True), -# ("asdf", ["qwer", "zxcv"], False) -# ]) + ("asdf", ["qwer", "asdf", "zxcv"], True), + ("asdf", ["qwer", "zxcv"], False) + ]) -# def test_is_fuzzy_match_to_list(str_to_match, list_to_matched, is_match): -# assert is_fuzzy_match_to_list(str_to_match, list_to_matched) == is_match +def test_is_fuzzy_match_to_list(str_to_match, list_to_matched, is_match): + assert is_fuzzy_match_to_list(str_to_match, list_to_matched) == is_match -# @pytest.mark.parametrize("str_to_match, list_to_matched, matches", [ +@pytest.mark.parametrize("str_to_match, list_to_matched, matches", [ -# ("asdf", ["qwer", "asdf", "zxcv"], [(1,"asdf")]), -# ("asdf", ["qwer", "zxcv"], []) -# ]) + ("asdf", ["qwer", "asdf", "zxcv"], [(1,"asdf")]), + ("asdf", ["qwer", "zxcv"], []) + ]) -# def test_fuzzy_matches_to_list(str_to_match, list_to_matched, matches): -# assert fuzzy_matches_to_list(str_to_match, list_to_matched) == matches +def test_fuzzy_matches_to_list(str_to_match, list_to_matched, matches): + assert fuzzy_matches_to_list(str_to_match, list_to_matched) == matches -# @pytest.mark.parametrize("pub_id, title, titles, is_in_pub_dict", [ +@pytest.mark.parametrize("pub_id, title, titles, is_in_pub_dict", [ -# ("https://doi.org/10.1016/j.chroma.2021.462426", "asdf", [], True), -# ("asdf", "Direct injection analysis of per and polyfluoroalkyl substances in surface and drinking water by sample filtration and liquid chromatography-tandem mass spectrometry.", -# ["Direct injection analysis of per and polyfluoroalkyl substances in surface and drinking water by sample filtration and liquid chromatography-tandem mass spectrometry.", -# "Untargeted Stable Isotope Probing of the Gut Microbiota Metabolome Using 13C-Labeled Dietary Fibers."], True), -# ("asdf", "qwer", [], False) -# ]) + ("https://doi.org/10.1016/j.chroma.2021.462426", "asdf", [], True), + ("asdf", "Direct injection analysis of per and polyfluoroalkyl substances in surface and drinking water by sample filtration and liquid chromatography-tandem mass spectrometry.", + ["Direct injection analysis of per and polyfluoroalkyl substances in surface and drinking water by sample filtration and liquid chromatography-tandem mass spectrometry.", + "Untargeted Stable Isotope Probing of the Gut Microbiota Metabolome Using 13C-Labeled Dietary Fibers."], True), + ("asdf", "qwer", [], False) + ]) -# def test_is_pub_in_publication_dict(pub_id, title, publication_dict, titles, is_in_pub_dict): -# assert is_pub_in_publication_dict(pub_id, title, publication_dict, titles) == is_in_pub_dict +def test_is_pub_in_publication_dict(pub_id, title, publication_dict, titles, is_in_pub_dict): + assert is_pub_in_publication_dict(pub_id, title, publication_dict, titles) == is_in_pub_dict -# def test_create_authors_by_project_dict(passing_config, authors_json_file, authors_by_project_dict, capsys): - -# authors_by_project_dict_check = create_authors_by_project_dict(passing_config) -# captured = capsys.readouterr() - -# assert authors_by_project_dict_check == authors_by_project_dict and captured.out == "Warning: The author, Isabel Escobar, in the project 1 project of the project tracking configuration file could not be found in the Authors section of the Configuration JSON file.\n" - - - -# def test_adjust_author_attributes(authors_by_project_dict, passing_config): - -# authors_by_project_dict["project 1"]["Hunter Moseley"]["affiliations"] = ["asdf"] -# authors_by_project_dict["project 1"]["Hunter Moseley"]["grants"] = ["asdf", "qwer"] -# authors_by_project_dict["project 1"]["Hunter Moseley"]["cutoff_year"] = 2000 - -# # del authors_by_project_dict["project 2"]["Hunter Moseley"]["affiliations"] -# # del authors_by_project_dict["project 2"]["Hunter Moseley"]["grants"] -# # del authors_by_project_dict["project 2"]["Hunter Moseley"]["cutoff_year"] - -# modified_authors_json_file = {'Andrew Morris': {'ORCID': '0000-0003-1910-4865', -# 'affiliations': ['kentucky'], -# 'collaborator_report': {}, -# 'cutoff_year': 2020, -# 'email': 'a.j.morris@uky.edu', -# 'first_name': 'Andrew', -# 'last_name': 'Morris', -# 'pubmed_name_search': 'Andrew Morris', -# 'scholar_id': '-j7fxnEAAAAJ', -# 'grants': ['P42 ES007380', 'P42ES007380']}, -# 'Hunter Moseley': {'ORCID': '0000-0003-3995-5368', -# 'affiliations': ['asdf', 'kentucky'], -# 'collaborator_report': {}, -# 'cutoff_year': 2000, -# 'email': 'hunter.moseley@gmail.com', -# 'first_name': 'Hunter', -# 'last_name': 'Moseley', -# 'pubmed_name_search': 'Hunter Moseley', -# 'scholar_id': 'ctE_FZMAAAAJ', -# 'grants': ['P42 ES007380', 'P42ES007380', 'asdf', 'qwer']}} +def test_create_authors_by_project_dict(passing_config, authors_json_file, authors_by_project_dict, capsys): + + authors_by_project_dict_check = create_authors_by_project_dict(passing_config) + captured = capsys.readouterr() + + assert authors_by_project_dict_check == authors_by_project_dict and captured.out == "Warning: The author, Isabel Escobar, in the project 1 project of the project tracking configuration file could not be found in the Authors section of the Configuration JSON file.\n" + + + +def test_adjust_author_attributes(authors_by_project_dict, passing_config): + + authors_by_project_dict["project 1"]["Hunter Moseley"]["affiliations"] = ["asdf"] + authors_by_project_dict["project 1"]["Hunter Moseley"]["grants"] = ["asdf", "qwer"] + authors_by_project_dict["project 1"]["Hunter Moseley"]["cutoff_year"] = 2000 + +# del authors_by_project_dict["project 2"]["Hunter Moseley"]["affiliations"] +# del authors_by_project_dict["project 2"]["Hunter Moseley"]["grants"] +# del authors_by_project_dict["project 2"]["Hunter Moseley"]["cutoff_year"] + + modified_authors_json_file = {'Andrew Morris': {'ORCID': '0000-0003-1910-4865', + 'affiliations': ['kentucky'], + 'collaborator_report': {}, + 'cutoff_year': 2020, + 'email': 'a.j.morris@uky.edu', + 'first_name': 'Andrew', + 'last_name': 'Morris', + 'pubmed_name_search': 'Andrew Morris', + 'scholar_id': '-j7fxnEAAAAJ', + 'grants': ['P42 ES007380', 'P42ES007380']}, + 'Hunter Moseley': {'ORCID': '0000-0003-3995-5368', + 'affiliations': ['asdf', 'kentucky'], + 'collaborator_report': {}, + 'cutoff_year': 2000, + 'email': 'hunter.moseley@gmail.com', + 'first_name': 'Hunter', + 'last_name': 'Moseley', + 'pubmed_name_search': 'Hunter Moseley', + 'scholar_id': 'ctE_FZMAAAAJ', + 'grants': ['P42 ES007380', 'P42ES007380', 'asdf', 'qwer']}} -# adjust_author_attributes(authors_by_project_dict, passing_config) + adjust_author_attributes(authors_by_project_dict, passing_config) -# assert passing_config["Authors"] == modified_authors_json_file + assert passing_config["Authors"] == modified_authors_json_file -# @pytest.fixture -# def tokenized_citations(): -# return [{"PMID":"1234", "DOI":"ASDF", "title":"made up title"}, -# {"PMID":"", "DOI":"ASDF", "title":""}, -# {"PMID":"1234", "DOI":"ASDF", "title":""}, +@pytest.fixture +def tokenized_citations(): + return [{"PMID":"1234", "DOI":"ASDF", "title":"made up title"}, + {"PMID":"", "DOI":"ASDF", "title":""}, + {"PMID":"1234", "DOI":"ASDF", "title":""}, -# {"PMID":"", "DOI":"QWER", "title":""}, -# {"PMID":"", "DOI":"qwer", "title":""}, + {"PMID":"", "DOI":"QWER", "title":""}, + {"PMID":"", "DOI":"qwer", "title":""}, -# {"PMID":"4567", "DOI":"", "title":""}, -# {"PMID":"4567", "DOI":"", "title":""}, + {"PMID":"4567", "DOI":"", "title":""}, + {"PMID":"4567", "DOI":"", "title":""}, -# {"PMID":"", "DOI":"", "title":"new title"}, -# {"PMID":"", "DOI":"", "title":"new titles"},] + {"PMID":"", "DOI":"", "title":"new title"}, + {"PMID":"", "DOI":"", "title":"new titles"},] -# def test_find_duplicate_citations(tokenized_citations): +def test_find_duplicate_citations(tokenized_citations): -# duplicate_citations_check = set([(0,1,2), (3,4), (5,6), (7,8)]) + duplicate_citations_check = set([(0,1,2), (3,4), (5,6), (7,8)]) -# duplicate_citations = find_duplicate_citations(tokenized_citations) + duplicate_citations = find_duplicate_citations(tokenized_citations) -# duplicate_citations = {tuple(duplicates) for duplicates in duplicate_citations} + duplicate_citations = {tuple(duplicates) for duplicates in duplicate_citations} -# assert duplicate_citations == duplicate_citations_check + assert duplicate_citations == duplicate_citations_check -# @pytest.fixture -# def publication_json(): -# return load_json(os.path.join("tests", "testing_files", "publication_dict.json")) +@pytest.fixture +def publication_json(): + return load_json(os.path.join("tests", "testing_files", "publication_dict.json")) -# def test_are_citations_in_pub_dict(publication_json): +def test_are_citations_in_pub_dict(publication_json): -# tokenized_citations = [{"PMID":"35313030", "DOI":"", "title":""}, -# {"PMID":"", "DOI":"10.1038/s41467-023-35784-x", "title":""}, -# {"PMID":"", "DOI":"", "title":"kegg_pull: a software package for the RESTful access and pulling from the Kyoto Encyclopedia of Gene and Genomes."}, -# {"PMID":"1234", "DOI":"", "title":""}] + tokenized_citations = [{"PMID":"35313030", "DOI":"", "title":""}, + {"PMID":"", "DOI":"10.1038/s41467-023-35784-x", "title":""}, + {"PMID":"", "DOI":"", "title":"kegg_pull: a software package for the RESTful access and pulling from the Kyoto Encyclopedia of Gene and Genomes."}, + {"PMID":"1234", "DOI":"", "title":""}] -# is_citation_in_pubs_check = [True, True, True, False] + is_citation_in_pubs_check = [True, True, True, False] -# is_citation_in_pubs = are_citations_in_pub_dict(tokenized_citations, publication_json) + is_citation_in_pubs = are_citations_in_pub_dict(tokenized_citations, publication_json) -# assert is_citation_in_pubs == is_citation_in_pubs_check + assert is_citation_in_pubs == is_citation_in_pubs_check diff --git a/tests/test_ref_srch_emails_and_reports.py b/tests/test_ref_srch_emails_and_reports.py index eaaab0c..2ae33f0 100644 --- a/tests/test_ref_srch_emails_and_reports.py +++ b/tests/test_ref_srch_emails_and_reports.py @@ -124,14 +124,14 @@ def config_dict(): 'Last Author': '', 'Pub_Authors': ', ', 'References': 'Citation: , Title: , PMID: , PMCID: , DOI: '}, - "column_order":['Authors', 'Grants', 'Abstract', 'Conclusions', 'Copyrights', 'DOI', 'Journal', 'Keywords', 'Methods', - 'PMID', 'Results', 'Title', 'PMCID', 'Publication Year', 'Publication Month', 'Publication Day', - 'Tok Title', 'Tok DOI', 'Tok PMID', 'Tok Authors', 'Ref Line', 'Comparison', 'First Author', - 'Last Author', 'Pub_Authors', 'References'], - "sort":["Authors"], - "file_format":"csv", - "filename":"test_name.csv", - "separator":"\t"}} + "column_order":['Authors', 'Grants', 'Abstract', 'Conclusions', 'Copyrights', 'DOI', 'Journal', 'Keywords', 'Methods', + 'PMID', 'Results', 'Title', 'PMCID', 'Publication Year', 'Publication Month', 'Publication Day', + 'Tok Title', 'Tok DOI', 'Tok PMID', 'Tok Authors', 'Ref Line', 'Comparison', 'First Author', + 'Last Author', 'Pub_Authors', 'References'], + "sort":["Authors"], + "file_format":"csv", + "filename":"test_name.csv", + "separator":"\t"}} return config_dict @@ -195,13 +195,12 @@ def test_create_tabular_report_excel(publication_dict, tokenized_citations, conf report, filename = create_tabular_report(publication_dict, config_dict, [], tokenized_citations, TESTING_DIR) actual_text = pandas.read_excel(os.path.join(TESTING_DIR, filename)) - # actual_text.to_excel(os.path.join("tests", "testing_files", "ref_srch_report_tabular4_new.xlsx")) + # actual_text.to_excel(os.path.join("tests", "testing_files", "ref_srch_report_tabular4_new.xlsx"), index=False) assert expected_text.to_csv() == actual_text.to_csv() - def test_create_tokenization_report(tokenized_citations): tokenized_citations.append({"authors":[], "title":"", "DOI":"", "PMID":"", "reference_line":""}) diff --git a/tests/test_ref_srch_modularized.py b/tests/test_ref_srch_modularized.py index 68035f0..cfe8c49 100644 --- a/tests/test_ref_srch_modularized.py +++ b/tests/test_ref_srch_modularized.py @@ -13,7 +13,7 @@ from academic_tracker.ref_srch_modularized import input_reading_and_checking, build_publication_dict, save_and_send_reports_and_emails from academic_tracker.fileio import load_json, read_text_from_txt -from academic_tracker.ref_srch_webio import search_references_on_PubMed, search_references_on_Crossref +from academic_tracker.ref_srch_webio import search_references_on_source @pytest.fixture(autouse=True) @@ -115,11 +115,11 @@ def test_input_reading_and_checking_noPubMed(config_dict): def test_build_publication_dict_with_Crossref(mocker, config_dict_Hunter_only, original_queries, tokenized_citations): # running_pubs = {} - # running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_PubMed(running_pubs, tokenized_citations, "asdf", original_queries["PubMed"]) - # running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_Crossref(copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["Crossref"]) + # running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_source("PubMed", running_pubs, tokenized_citations, "asdf", original_queries["PubMed"]) + # running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_source("Crossref", copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["Crossref"]) - # running_pubs3, matching_key_for_citation3, all_pubs = search_references_on_PubMed(copy.deepcopy(running_pubs2), tokenized_citations, "asdf", original_queries["PubMed"]) - # running_pubs4, matching_key_for_citation4, all_pubs = search_references_on_Crossref(copy.deepcopy(running_pubs3), tokenized_citations, "asdf", original_queries["Crossref"]) + # running_pubs3, matching_key_for_citation3, all_pubs = search_references_on_source("PubMed", copy.deepcopy(running_pubs2), tokenized_citations, "asdf", original_queries["PubMed"]) + # running_pubs4, matching_key_for_citation4, all_pubs = search_references_on_source("Crossref", copy.deepcopy(running_pubs3), tokenized_citations, "asdf", original_queries["Crossref"]) # with open(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "all", "running_pubs1.json"),'w') as jsonFile: @@ -150,14 +150,11 @@ def test_build_publication_dict_with_Crossref(mocker, config_dict_Hunter_only, o matching_key_for_citation3 = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "all", "matching_key_for_citation3.json")) matching_key_for_citation4 = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "all", "matching_key_for_citation4.json")) - mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_PubMed", + mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_source", side_effect=[(running_pubs1, matching_key_for_citation1, original_queries["PubMed"]), - (running_pubs3, matching_key_for_citation3, original_queries["PubMed"])]) - - mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_Crossref", - side_effect=[(running_pubs2, matching_key_for_citation2, original_queries["Crossref"]), - (running_pubs4, matching_key_for_citation4, original_queries["Crossref"])]) - + (running_pubs2, matching_key_for_citation2, original_queries["Crossref"]), + (running_pubs3, matching_key_for_citation3, original_queries["PubMed"]), + (running_pubs4, matching_key_for_citation4, original_queries["Crossref"])]) actual_publication_dict, actual_tokenized_citations, _ = build_publication_dict(config_dict_Hunter_only, tokenized_citations, False, False) @@ -181,9 +178,9 @@ def test_build_publication_dict_with_Crossref(mocker, config_dict_Hunter_only, o def test_build_publication_dict_no_Crossref(mocker, config_dict_Hunter_only, original_queries, tokenized_citations): # running_pubs = {} - # running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_PubMed(running_pubs, tokenized_citations, "asdf", original_queries["PubMed"]) + # running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_source("PubMed", running_pubs, tokenized_citations, "asdf", original_queries["PubMed"]) - # running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_PubMed(copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["PubMed"]) + # running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_source("PubMed", copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["PubMed"]) # with open(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "running_pubs1.json"),'w') as jsonFile: @@ -202,7 +199,7 @@ def test_build_publication_dict_no_Crossref(mocker, config_dict_Hunter_only, ori matching_key_for_citation1 = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "matching_key_for_citation1.json")) matching_key_for_citation2 = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "matching_key_for_citation2.json")) - mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_PubMed", + mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_source", side_effect=[(running_pubs1, matching_key_for_citation1, original_queries["PubMed"]), (running_pubs2, matching_key_for_citation2, original_queries["PubMed"])]) @@ -230,9 +227,9 @@ def test_build_publication_dict_no_Crossref(mocker, config_dict_Hunter_only, ori def test_build_publication_dict_no_PubMed(mocker, config_dict_Hunter_only, original_queries, tokenized_citations): # running_pubs = {} - # running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_Crossref(running_pubs, tokenized_citations, "asdf", original_queries["Crossref"]) + # running_pubs1, matching_key_for_citation1, all_pubs = search_references_on_source("Crossref", running_pubs, tokenized_citations, "asdf", original_queries["Crossref"]) - # running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_Crossref(copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["Crossref"]) + # running_pubs2, matching_key_for_citation2, all_pubs = search_references_on_source("Crossref", copy.deepcopy(running_pubs1), tokenized_citations, "asdf", original_queries["Crossref"]) # with open(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "running_pubs1.json"),'w') as jsonFile: @@ -251,7 +248,7 @@ def test_build_publication_dict_no_PubMed(mocker, config_dict_Hunter_only, origi matching_key_for_citation1 = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "matching_key_for_citation1.json")) matching_key_for_citation2 = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "matching_key_for_citation2.json")) - mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_Crossref", + mocker.patch("academic_tracker.ref_srch_modularized.ref_srch_webio.search_references_on_source", side_effect=[(running_pubs1, matching_key_for_citation1, original_queries["Crossref"]), (running_pubs2, matching_key_for_citation2, original_queries["Crossref"])]) diff --git a/tests/test_ref_srch_webio_no_internet.py b/tests/test_ref_srch_webio_no_internet.py index 5a8f46e..f29c2ff 100644 --- a/tests/test_ref_srch_webio_no_internet.py +++ b/tests/test_ref_srch_webio_no_internet.py @@ -9,7 +9,7 @@ import requests import xml.etree.ElementTree as ET -from academic_tracker.ref_srch_webio import build_pub_dict_from_PMID, search_references_on_PubMed, search_references_on_Crossref +from academic_tracker.ref_srch_webio import build_pub_dict_from_PMID, search_references_on_source from academic_tracker.ref_srch_webio import parse_myncbi_citations, tokenize_reference_input from academic_tracker.fileio import load_json, read_text_from_txt @@ -31,6 +31,16 @@ def pymed_query(): return articles +@pytest.fixture +def original_queries(): + query_json = load_json(os.path.join("tests", "testing_files", "all_queries_ref.json")) + ## Convert PubMed dictionaries back to articles class. + for i, pub_list in enumerate(query_json["PubMed"]): + new_list = [] + for pub in pub_list: + new_list.append(pymed.article.PubMedArticle(ET.fromstring(pub["xml"]))) + query_json["PubMed"][i] = new_list + return query_json def test_build_pub_dict_from_PMID(pymed_query, mocker): @@ -59,6 +69,14 @@ def tokenized_citations(): return [tokenized_citations[i] for i in [6,8,63]] +def test_search_references_on_source_unknown_source(capsys): + with pytest.raises(SystemExit): + search_references_on_source("asdf", {}, [], "ptth222@uky.edu") + captured = capsys.readouterr() + + assert captured.out == "Error: When searching references there was an attempt to query an unknown source, 'asdf'.\n" + + def test_search_references_on_PubMed(tokenized_citations, ref_pymed_query, mocker): def mock_query(*args, **kwargs): @@ -68,7 +86,7 @@ def mock_query(*args, **kwargs): expected_publication_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_publication_dict.json")) expected_citation_keys = load_json(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations.json")) - actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_PubMed({}, tokenized_citations, "ptth222@uky.edu") + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("PubMed", {}, tokenized_citations, "ptth222@uky.edu") # with open(os.path.join("tests", "testing_files", "ref_srch_publication_dict_new.json"),'w') as jsonFile: # jsonFile.write(json.dumps(actual_publication_dict, indent=2, sort_keys=True)) # with open(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_new.json"),'w') as jsonFile: @@ -76,9 +94,93 @@ def mock_query(*args, **kwargs): assert expected_publication_dict == actual_publication_dict assert expected_citation_keys == actual_citation_keys + + +def test_search_references_on_PubMed_merge(original_queries): + running_pubs = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "publication_dict.json")) + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "tokenized_reference.json")) + + expected_publication_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_publication_dict_PubMed_merge.json")) + expected_citation_keys = load_json(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_PubMed_merge.json")) + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("PubMed", running_pubs, tokenized_citations, "ptth222@uky.edu", original_queries["PubMed"]) + # with open(os.path.join("tests", "testing_files", "ref_srch_publication_dict_PubMed_merge_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_publication_dict, indent=2, sort_keys=True)) + # with open(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_PubMed_merge_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_citation_keys, indent=2, sort_keys=True)) + + assert expected_publication_dict == actual_publication_dict + assert expected_citation_keys == actual_citation_keys + + +def test_search_references_on_PubMed_unsearchable_citation(original_queries, mocker): + def mock_query(*args, **kwargs): + return ref_pymed_query + mocker.patch("academic_tracker.ref_srch_webio.pymed.PubMed.query", mock_query) + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "tokenized_reference.json")) + tokenized_citations = [tokenized_citations[0]] + tokenized_citations[0]["PMID"] = None + tokenized_citations[0]["DOI"] = None + tokenized_citations[0]["title"] = None + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("PubMed", {}, tokenized_citations, "ptth222@uky.edu") + + assert {} == actual_publication_dict + assert [None] == actual_citation_keys +def test_search_references_on_PubMed_non_article(original_queries): + running_pubs = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "publication_dict.json")) + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "tokenized_reference.json")) + + expected_publication_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_publication_dict_PubMed_merge.json")) + del expected_publication_dict["https://doi.org/10.1007/978-1-4939-1258-2_11"] + expected_citation_keys = load_json(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_PubMed_merge.json")) + expected_citation_keys[2] = None + + ## Make a query not a dict to trigger a continue. + original_queries["PubMed"][2][0] = original_queries["PubMed"][2][0].toDict() + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("PubMed", running_pubs, tokenized_citations, "ptth222@uky.edu", original_queries["PubMed"]) + + assert expected_publication_dict == actual_publication_dict + assert expected_citation_keys == actual_citation_keys + + +def test_search_references_on_PubMed_title_match(original_queries): + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "tokenized_reference.json")) + tokenized_citations = [tokenized_citations[0]] + tokenized_citations[0]["PMID"] = None + tokenized_citations[0]["DOI"] = None + + expected_publication_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_publication_dict_PubMed_title_match.json")) + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("PubMed", {}, tokenized_citations, "ptth222@uky.edu", original_queries["PubMed"]) + # with open(os.path.join("tests", "testing_files", "ref_srch_publication_dict_PubMed_title_match_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_publication_dict, indent=2, sort_keys=True)) + + assert expected_publication_dict == actual_publication_dict + assert ['https://doi.org/10.3390/metabo3040853'] == actual_citation_keys + + +def test_search_references_on_PubMed_duplicate_citation(original_queries): + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_PubMed", "tokenized_reference.json")) + tokenized_citations = [tokenized_citations[0], tokenized_citations[0]] + + original_queries["PubMed"] = [original_queries["PubMed"][0], original_queries["PubMed"][0]] + + expected_publication_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_publication_dict_PubMed_duplicate_citation.json")) + expected_citation_keys = load_json(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_PubMed_duplicate_citation.json")) + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("PubMed", {}, tokenized_citations, "ptth222@uky.edu", original_queries["PubMed"]) + # with open(os.path.join("tests", "testing_files", "ref_srch_publication_dict_PubMed_duplicate_citation_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_publication_dict, indent=2, sort_keys=True)) + # with open(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_PubMed_duplicate_citation_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_citation_keys, indent=2, sort_keys=True)) + + assert expected_publication_dict == actual_publication_dict + assert expected_citation_keys == actual_citation_keys + def test_search_references_on_Crossref(tokenized_citations, mocker): def query_generator(): @@ -95,7 +197,7 @@ def mock_query(*args, **kwargs): expected_pub_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_Crossref_pub_dict.json")) expected_citation_keys = load_json(os.path.join("tests", "testing_files", "ref_srch_Crossref_keys_for_citations.json")) - actual_pub_dict, actual_citation_keys, all_pubs = search_references_on_Crossref({}, tokenized_citations, "ptth222@uky.edu") + actual_pub_dict, actual_citation_keys, all_pubs = search_references_on_source("Crossref", {}, tokenized_citations, "ptth222@uky.edu") # with open(os.path.join("tests", "testing_files", "ref_srch_Crossref_pub_dict_new.json"),'w') as jsonFile: # jsonFile.write(json.dumps(actual_pub_dict, indent=2, sort_keys=True)) # with open(os.path.join("tests", "testing_files", "ref_srch_Crossref_keys_for_citations_new.json"),'w') as jsonFile: @@ -105,6 +207,109 @@ def mock_query(*args, **kwargs): assert actual_citation_keys == expected_citation_keys +def test_search_references_on_Crossref_merge(original_queries): + running_pubs = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "publication_dict.json")) + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "tokenized_reference.json")) + + expected_publication_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_publication_dict_Crossref_merge.json")) + expected_citation_keys = load_json(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_Crossref_merge.json")) + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("Crossref", running_pubs, tokenized_citations, "ptth222@uky.edu", original_queries["Crossref"]) + # with open(os.path.join("tests", "testing_files", "ref_srch_publication_dict_Crossref_merge_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_publication_dict, indent=2, sort_keys=True)) + # with open(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_Crossref_merge_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_citation_keys, indent=2, sort_keys=True)) + + assert expected_publication_dict == actual_publication_dict + assert expected_citation_keys == actual_citation_keys + + +def test_search_references_on_Crossref_unsearchable_citation(original_queries, mocker): + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "tokenized_reference.json")) + tokenized_citations = [tokenized_citations[0]] + tokenized_citations[0]["PMID"] = None + tokenized_citations[0]["DOI"] = None + tokenized_citations[0]["title"] = None + + mock_crossref = mocker.MagicMock() + mock_crossref.configure_mock( + **{ + "works.return_value": {"message":{"items":original_queries["Crossref"][0]}} + } + ) + + mocker.patch("academic_tracker.ref_srch_webio.habanero.Crossref", + side_effect=[mock_crossref]) + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("Crossref", {}, tokenized_citations, "ptth222@uky.edu", None) + + assert {} == actual_publication_dict + assert [None] == actual_citation_keys + + +def test_search_references_on_Crossref_no_pub_id(original_queries, mocker, capsys): + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "tokenized_reference.json")) + tokenized_citations = [tokenized_citations[0]] + + modified_query = original_queries["Crossref"][0] + del modified_query[0]["DOI"] + del modified_query[0]["URL"] + del modified_query[0]["link"] + + mock_crossref = mocker.MagicMock() + mock_crossref.configure_mock( + **{ + "works.return_value": {"message":{"items":modified_query}} + } + ) + + mocker.patch("academic_tracker.ref_srch_webio.habanero.Crossref", + side_effect=[mock_crossref]) + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("Crossref", {}, tokenized_citations, "ptth222@uky.edu", None) + captured = capsys.readouterr() + + assert {} == actual_publication_dict + assert [None] == actual_citation_keys + assert captured.out == ("Warning: Could not find a DOI or external URL for a publication when " + "searching Crossref. It will not be in the publications.\n" + "Title: A Computational Framework for High-Throughput Isotopic " + "Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets\n") + + +def test_search_references_on_Crossref_title_match(original_queries): + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "tokenized_reference.json")) + tokenized_citations = [tokenized_citations[0]] + tokenized_citations[0]["PMID"] = None + tokenized_citations[0]["DOI"] = None + + expected_publication_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_publication_dict_Crossref_title_match.json")) + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("Crossref", {}, tokenized_citations, "ptth222@uky.edu", original_queries["Crossref"]) + # with open(os.path.join("tests", "testing_files", "ref_srch_publication_dict_Crossref_title_match_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_publication_dict, indent=2, sort_keys=True)) + + assert expected_publication_dict == actual_publication_dict + assert ['https://doi.org/10.3390/metabo3040853'] == actual_citation_keys + + +def test_search_references_on_Crossref_duplicate_citation(original_queries): + tokenized_citations = load_json(os.path.join("tests", "testing_files", "intermediate_results", "ref_search", "no_Crossref", "tokenized_reference.json")) + tokenized_citations = [tokenized_citations[0], tokenized_citations[0]] + + original_queries["Crossref"] = [original_queries["Crossref"][0], original_queries["Crossref"][0]] + + expected_publication_dict = load_json(os.path.join("tests", "testing_files", "ref_srch_publication_dict_Crossref_duplicate_citation.json")) + expected_citation_keys = load_json(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_Crossref_duplicate_citation.json")) + + actual_publication_dict, actual_citation_keys, all_pubs = search_references_on_source("Crossref", {}, tokenized_citations, "ptth222@uky.edu", original_queries["Crossref"]) + # with open(os.path.join("tests", "testing_files", "ref_srch_publication_dict_Crossref_duplicate_citation_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_publication_dict, indent=2, sort_keys=True)) + # with open(os.path.join("tests", "testing_files", "ref_srch_keys_for_citations_Crossref_duplicate_citation_new.json"),'w') as jsonFile: + # jsonFile.write(json.dumps(actual_citation_keys, indent=2, sort_keys=True)) + + assert expected_publication_dict == actual_publication_dict + assert expected_citation_keys == actual_citation_keys def test_parse_myncbi_citations(mocker): @@ -128,13 +333,48 @@ def mock_query(*args, **kwargs): assert expected_tokenized_citations == actual_tokenized_citations +def test_parse_myncbi_citations_bad_web_address(mocker, capsys): + def mock_query(*args, **kwargs): + return None + mocker.patch("academic_tracker.ref_srch_webio.webio.get_url_contents_as_str", mock_query) + + with pytest.raises(SystemExit): + parse_myncbi_citations("asdf") + captured = capsys.readouterr() + + assert captured.out == "Error: Could not access the MYNCBI webpage. Make sure the address is correct.\n" + + +def test_parse_myncbi_citations_bad_page(mocker, capsys): + def page_generator(): + pages = load_json(os.path.join("tests", "testing_files", "myncbi_webpages.json")) + for i, page in enumerate(pages): + if i == 1: + yield None + else: + yield page + + pages = page_generator() + + def mock_query(*args, **kwargs): + return next(pages) + mocker.patch("academic_tracker.ref_srch_webio.webio.get_url_contents_as_str", mock_query) + + with pytest.raises(SystemExit): + parse_myncbi_citations("asdf") + captured = capsys.readouterr() + + assert captured.out == "Error: Could not access page 2 of the MYNCBI webpage. Aborting run.\n" + + ## Test that the JSON read in works and finds and eliminates duplicates. def test_tokenize_reference_input_JSON(capsys): expected_tokenized_citations = load_json(os.path.join("tests", "testing_files", "tokenized_citations_duplicates_removed.json")) + expected_tokenized_citations[55]["reference_line"] = "" - actual_tokenized_citations = tokenize_reference_input(os.path.join("tests", "testing_files", "tokenized_citations.json"), False) + actual_tokenized_citations = tokenize_reference_input(os.path.join("tests", "testing_files", "tokenized_citations_missing_ref_line.json"), False) captured = capsys.readouterr() # with open(os.path.join("tests", "testing_files", "tokenized_citations_duplicates_removed_new.json"),'w') as jsonFile: # jsonFile.write(json.dumps(actual_tokenized_citations, indent=2, sort_keys=True)) @@ -232,6 +472,25 @@ def test_tokenize_reference_input_no_references(capsys): assert captured.out == "Warning: Could not tokenize any citations in provided reference. Check setup and formatting and try again.\n" +def test_tokenize_reference_input_myncbi(mocker): + def page_generator(): + pages = load_json(os.path.join("tests", "testing_files", "myncbi_webpages.json")) + for page in pages: + yield page + + pages = page_generator() + + def mock_query(*args, **kwargs): + return next(pages) + mocker.patch("academic_tracker.ref_srch_webio.webio.get_url_contents_as_str", mock_query) + + expected_tokenized_citations = load_json(os.path.join("tests", "testing_files", "tokenized_citations.json")) + + actual_tokenized_citations = tokenize_reference_input("https://www.asdf/ncbi.nlm.nih.gov/myncbi/", False, False) + + assert expected_tokenized_citations == actual_tokenized_citations + + diff --git a/tests/test_user_input_checking.py b/tests/test_user_input_checking.py index d59a52c..e7f31b9 100644 --- a/tests/test_user_input_checking.py +++ b/tests/test_user_input_checking.py @@ -43,6 +43,7 @@ def test_schema(): "wrong_pattern_test": {"type": "string", "pattern": "^asdf$"}, "other_error_type": {"type": "number", "exclusiveMaximum":100} }, + "dependentRequired":{"dependency":["dependent_field"]}, "required": ["required_test"] } @@ -61,6 +62,7 @@ def test_schema(): ({"required_test":{"required_test":""}, "wrong_type_test":123}, "ValidationError: An error was found in the Test Schema. \nThe value for ['wrong_type_test'] is not of type \"string\"."), ({"required_test":{"required_test":""}, "wrong_format_test":"asdf"}, "ValidationError: An error was found in the Test Schema. \nThe value for ['wrong_format_test'] is not a valid email."), ({"required_test":{"required_test":""}, "wrong_pattern_test":"qwer"}, "ValidationError: An error was found in the Test Schema. \nThe value for ['wrong_pattern_test'] did not fit the pattern."), + ({"required_test":{"required_test":""}, "dependency":""}, "ValidationError: An error was found in the Test Schema. \nThe entry [] is missing a dependent property.\n'dependent_field' is a dependency of 'dependency'"), ]) @@ -221,8 +223,8 @@ def test_config_file_project_report_sort_error_project(passing_config, capsys): passing_config["project_descriptions"]["project 1"]["project_report"] = {"columns":{"Name":"asdf"}, "sort":["asdf"]} error_message = "ValidationError: The \"sort\" attribute for the project_report in project project 1 " +\ - "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -233,8 +235,8 @@ def test_config_file_project_report_column_order_error_project(passing_config, c passing_config["project_descriptions"]["project 1"]["project_report"] = {"columns":{"Name":"asdf"}, "column_order":["asdf"]} error_message = "ValidationError: The \"column_order\" attribute for the project_report in project project 1 " +\ - "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -246,7 +248,7 @@ def test_config_file_project_report_column_order_error_not_all_names_project(pas "Title":"asdf"}, "column_order":["Name"]} error_message = "ValidationError: The \"column_order\" attribute for the project_report in project project 1 " +\ - "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." + "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -255,10 +257,10 @@ def test_config_file_project_report_column_order_error_not_all_names_project(pas def test_config_file_project_report_sort_error_author(passing_config, capsys): passing_config["Authors"]["Andrew Morris"]["project_report"] = {"columns":{"Name":"asdf"}, - "sort":["asdf"]} + "sort":["asdf"]} error_message = "ValidationError: The \"sort\" attribute for the project_report for author Andrew Morris " +\ - "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -267,10 +269,10 @@ def test_config_file_project_report_sort_error_author(passing_config, capsys): def test_config_file_project_report_column_order_error_author(passing_config, capsys): passing_config["Authors"]["Andrew Morris"]["project_report"] = {"columns":{"Name":"asdf"}, - "column_order":["asdf"]} + "column_order":["asdf"]} error_message = "ValidationError: The \"column_order\" attribute for the project_report for author Andrew Morris " +\ - "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -279,10 +281,10 @@ def test_config_file_project_report_column_order_error_author(passing_config, ca def test_config_file_project_report_column_order_error_not_all_names_author(passing_config, capsys): passing_config["Authors"]["Andrew Morris"]["project_report"] = {"columns":{"Name":"asdf", - "Title":"asdf"}, + "Title":"asdf"}, "column_order":["Name"]} error_message = "ValidationError: The \"column_order\" attribute for the project_report for author Andrew Morris " +\ - "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." + "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -330,8 +332,8 @@ def test_config_file_collaborator_report_sort_error_project(passing_config, caps passing_config["project_descriptions"]["project 1"]["collaborator_report"] = {"columns":{"Name":"asdf"}, "sort":["asdf"]} error_message = "ValidationError: The \"sort\" attribute for the collaborator_report in project project 1 " +\ - "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -342,8 +344,8 @@ def test_config_file_collaborator_report_column_order_error_project(passing_conf passing_config["project_descriptions"]["project 1"]["collaborator_report"] = {"columns":{"Name":"asdf"}, "column_order":["asdf"]} error_message = "ValidationError: The \"column_order\" attribute for the collaborator_report in project project 1 " +\ - "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -355,7 +357,7 @@ def test_config_file_collaborator_report_column_order_error_not_all_names_projec "Title":"asdf"}, "column_order":["Name"]} error_message = "ValidationError: The \"column_order\" attribute for the collaborator_report in project project 1 " +\ - "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." + "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -364,10 +366,10 @@ def test_config_file_collaborator_report_column_order_error_not_all_names_projec def test_config_file_collaborator_report_sort_error_author(passing_config, capsys): passing_config["Authors"]["Andrew Morris"]["collaborator_report"] = {"columns":{"Name":"asdf"}, - "sort":["asdf"]} + "sort":["asdf"]} error_message = "ValidationError: The \"sort\" attribute for the collaborator_report for author Andrew Morris " +\ - "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -376,10 +378,10 @@ def test_config_file_collaborator_report_sort_error_author(passing_config, capsy def test_config_file_collaborator_report_column_order_error_author(passing_config, capsys): passing_config["Authors"]["Andrew Morris"]["collaborator_report"] = {"columns":{"Name":"asdf"}, - "column_order":["asdf"]} + "column_order":["asdf"]} error_message = "ValidationError: The \"column_order\" attribute for the collaborator_report for author Andrew Morris " +\ - "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -388,10 +390,10 @@ def test_config_file_collaborator_report_column_order_error_author(passing_confi def test_config_file_collaborator_report_column_order_error_not_all_names_author(passing_config, capsys): passing_config["Authors"]["Andrew Morris"]["collaborator_report"] = {"columns":{"Name":"asdf", - "Title":"asdf"}, + "Title":"asdf"}, "column_order":["Name"]} error_message = "ValidationError: The \"column_order\" attribute for the collaborator_report for author Andrew Morris " +\ - "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." + "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -438,8 +440,8 @@ def test_config_file_summary_report_sort_error_project(passing_config, capsys): passing_config["summary_report"] = {"columns":{"Name":"asdf"}, "sort":["asdf"]} error_message = "ValidationError: The \"sort\" attribute for the summary_report " +\ - "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -450,8 +452,8 @@ def test_config_file_summary_report_column_order_error_project(passing_config, c passing_config["summary_report"] = {"columns":{"Name":"asdf"}, "column_order":["asdf"]} error_message = "ValidationError: The \"column_order\" attribute for the summary_report " +\ - "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -460,10 +462,10 @@ def test_config_file_summary_report_column_order_error_project(passing_config, c def test_config_file_summary_report_column_order_error_not_all_names_project(passing_config, capsys): passing_config["summary_report"] = {"columns":{"Name":"asdf", - "Title":"asdf"}, - "column_order":["Name"]} + "Title":"asdf"}, + "column_order":["Name"]} error_message = "ValidationError: The \"column_order\" attribute for the summary_report " +\ - "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." + "does not have all of the column names in \"columns\". Every column in \"columns\" must be in \"column_order\"." with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -665,8 +667,8 @@ def test_ref_config_file_summary_report_sort_error_project(passing_config, capsy passing_config["summary_report"] = {"columns":{"Name":"asdf"}, "sort":["asdf"]} error_message = "ValidationError: The \"sort\" attribute for the summary_report " +\ - "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"sort\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -677,8 +679,8 @@ def test_ref_config_file_summary_report_column_order_error_project(passing_confi passing_config["summary_report"] = {"columns":{"Name":"asdf"}, "column_order":["asdf"]} error_message = "ValidationError: The \"column_order\" attribute for the summary_report " +\ - "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ - "could not be matched to a column in \"columns\":\n\nasdf" + "has values that are not column names in \"columns\".\nThe following names in \"column_order\" " +\ + "could not be matched to a column in \"columns\":\n\nasdf" with pytest.raises(SystemExit): config_report_check(passing_config) captured = capsys.readouterr() @@ -764,24 +766,24 @@ def test_ref_config_file_check_schema_reduction(passing_config): def passing_pubs(): return {"30602735" : { 'abstract': "Following the publication of this article the authors noted that Torfi Sigurdsson's name was misspelled. Instead of Sigrudsson it should be Sigurdsson. The PDF and HTML versions of the paper have been modified accordingly.\xa0The authors would like to apologise for this error and the inconvenience this may have caused.", - 'authors': [ - { 'affiliation': 'Department of Neurology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany.', - 'firstname': 'Carine', - 'initials': 'C', - 'lastname': 'Thalman'},], - 'conclusions': None, - 'copyrights': None, - 'doi': '10.1038/s41380-018-0320-1', - 'journal': 'Molecular psychiatry', - 'keywords': [], - 'methods': None, - 'publication_date': {"year":2019, "month":1, "day":4}, - 'pubmed_id': '30602735', - 'results': None, - 'title': 'Correction: Synaptic phospholipids as a new target for cortical hyperexcitability and E/I balance in psychiatric disorders.', - 'grants':['P42 ES007380', 'P42 ES007381'], - 'PMCID':'PMC7933073'} - } + 'authors': [ + { 'affiliation': 'Department of Neurology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany.', + 'firstname': 'Carine', + 'initials': 'C', + 'lastname': 'Thalman'},], + 'conclusions': None, + 'copyrights': None, + 'doi': '10.1038/s41380-018-0320-1', + 'journal': 'Molecular psychiatry', + 'keywords': [], + 'methods': None, + 'publication_date': {"year":2019, "month":1, "day":4}, + 'pubmed_id': '30602735', + 'results': None, + 'title': 'Correction: Synaptic phospholipids as a new target for cortical hyperexcitability and E/I balance in psychiatric disorders.', + 'grants':['P42 ES007380', 'P42 ES007381'], + 'PMCID':'PMC7933073'} + } @pytest.mark.parametrize("pub_errors", [ ({"abstract":123}), @@ -840,11 +842,11 @@ def test_prev_pubs_file_check_missing_required_error(passing_pubs): @pytest.fixture def passing_tok(): return [{"authors": [{"last": "Last", "initials": "", "first": "First", "middle": ""}], - "title": "Pub Title", - "PMID": "", - "DOI": "", - "reference_line": "", - "pub_dict_key": ""}] + "title": "Pub Title", + "PMID": "", + "DOI": "", + "reference_line": "", + "pub_dict_key": ""}] @pytest.mark.parametrize("tok_errors", [ ({"authors":123}), diff --git a/tests/test_webio_no_internet.py b/tests/test_webio_no_internet.py index 7e15ebc..69e1715 100644 --- a/tests/test_webio_no_internet.py +++ b/tests/test_webio_no_internet.py @@ -10,7 +10,8 @@ from fixtures import authors_dict from academic_tracker.webio import search_ORCID_for_ids, search_Google_Scholar_for_ids -from academic_tracker.webio import get_DOI_from_Crossref, get_grants_from_Crossref +from academic_tracker.webio import get_DOI_from_Crossref +# from academic_tracker.webio import get_grants_from_Crossref from academic_tracker.fileio import load_json @@ -51,7 +52,7 @@ def mock_token(*args, **kwargs): mocker.patch("academic_tracker.webio.orcid.PublicAPI.get_search_token_from_orcid", mock_token) del authors_dict["Andrew Morris"]["affiliations"] - authors_dict["Andrew Morris"]["ORCID"] == "" + authors_dict["Andrew Morris"]["ORCID"] = "" authors_dict_check = copy.deepcopy(authors_dict) @@ -67,7 +68,7 @@ def mock_token(*args, **kwargs): return "sdfg" mocker.patch("academic_tracker.webio.orcid.PublicAPI.get_search_token_from_orcid", mock_token) - authors_dict["Andrew Morris"]["ORCID"] == "" + authors_dict["Andrew Morris"]["ORCID"] = "" authors_dict_check = copy.deepcopy(authors_dict) @@ -83,8 +84,8 @@ def mock_token(*args, **kwargs): return "sdfg" mocker.patch("academic_tracker.webio.orcid.PublicAPI.get_search_token_from_orcid", mock_token) - authors_dict["Andrew Morris"]["ORCID"] == "" - authors_dict["Andrew Morris"]["affiliations"] == ["Bristol"] + authors_dict["Andrew Morris"]["ORCID"] = "" + authors_dict["Andrew Morris"]["affiliations"] = ["Bristol"] authors_dict_check = copy.deepcopy(authors_dict) authors_dict_check["Andrew Morris"]["ORCID"] = "0000-0003-1910-4865" @@ -115,7 +116,7 @@ def mock_queried_author(*args, **kwargs): mocker.patch("academic_tracker.webio.scholarly.scholarly.search_author", mock_queried_author) del authors_dict["Andrew Morris"]["affiliations"] - authors_dict["Andrew Morris"]["scholar_id"] == "" + authors_dict["Andrew Morris"]["scholar_id"] = "" authors_dict_check = copy.deepcopy(authors_dict) @@ -127,11 +128,10 @@ def mock_queried_author(*args, **kwargs): return scholarly_authors mocker.patch("academic_tracker.webio.scholarly.scholarly.search_author", mock_queried_author) - authors_dict["Andrew Morris"]["scholar_id"] == "" - authors_dict["Andrew Morris"]["first_name"] == "asdf" + authors_dict["Andrew Morris"]["scholar_id"] = "" + authors_dict["Andrew Morris"]["first_name"] = "asdf" authors_dict_check = copy.deepcopy(authors_dict) - authors_dict_check["Andrew Morris"]["scholar_id"] == "-j7fxnEAAAAJ" assert search_Google_Scholar_for_ids(authors_dict) == authors_dict_check @@ -141,9 +141,10 @@ def mock_queried_author(*args, **kwargs): return scholarly_authors mocker.patch("academic_tracker.webio.scholarly.scholarly.search_author", mock_queried_author) - authors_dict["Andrew Morris"]["scholar_id"] == "" + authors_dict["Andrew Morris"]["scholar_id"] = "" authors_dict_check = copy.deepcopy(authors_dict) + authors_dict_check["Andrew Morris"]["scholar_id"] = "-j7fxnEAAAAJ" assert search_Google_Scholar_for_ids(authors_dict) == authors_dict_check @@ -167,20 +168,21 @@ def mock_query(*args, **kwargs): assert get_DOI_from_Crossref("asdfasdf", "ptth222@uky.edu") == None -def test_get_grants_from_Crossref_grants_found(mocker): - def mock_query(*args, **kwargs): - return load_json(os.path.join("tests", "testing_files", "Crossref_grant_query.json")) - mocker.patch("academic_tracker.webio.habanero.Crossref.works", mock_query) +## This function is unused in the actual code. +# def test_get_grants_from_Crossref_grants_found(mocker): +# def mock_query(*args, **kwargs): +# return load_json(os.path.join("tests", "testing_files", "Crossref_grant_query.json")) +# mocker.patch("academic_tracker.webio.habanero.Crossref.works", mock_query) - assert get_grants_from_Crossref("Multifunctional temperature\u2010responsive polymers as advanced biomaterials and beyond", "ptth222@uky.edu", ['P42ES007380']) == ['P42ES007380'] +# assert get_grants_from_Crossref("Multifunctional temperature\u2010responsive polymers as advanced biomaterials and beyond", "ptth222@uky.edu", ['P42ES007380']) == ['P42ES007380'] -def test_get_grants_from_Crossref_grants_not_found(mocker): - def mock_query(*args, **kwargs): - return load_json(os.path.join("tests", "testing_files", "Crossref_grant_query.json")) - mocker.patch("academic_tracker.webio.habanero.Crossref.works", mock_query) +# def test_get_grants_from_Crossref_grants_not_found(mocker): +# def mock_query(*args, **kwargs): +# return load_json(os.path.join("tests", "testing_files", "Crossref_grant_query.json")) +# mocker.patch("academic_tracker.webio.habanero.Crossref.works", mock_query) - assert get_grants_from_Crossref("asdfasdf", "ptth222@uky.edu", ['P42ES007380']) == None +# assert get_grants_from_Crossref("asdfasdf", "ptth222@uky.edu", ['P42ES007380']) == None diff --git a/tests/testing_files/Crossref_merge.json b/tests/testing_files/Crossref_merge.json index 8c9166b..00f7bcf 100644 --- a/tests/testing_files/Crossref_merge.json +++ b/tests/testing_files/Crossref_merge.json @@ -191,8 +191,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 16, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -211,21 +211,21 @@ { "PMCID": null, "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom, A. L. et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS). Sci. Total Envir. 778, 146192 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen, T. et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 1172, 122653 (2021).", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -239,98 +239,98 @@ { "PMCID": null, "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton, S. E. et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 40, 606\u2013630 (2021).", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk, K. H., Darlington, R., Benotti, M., Deeb, R. & Hawley, E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 204, 757\u2013764 (2017).", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. https://doi.org/10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman, M. F., Peldszus, S. & Anderson, W. B. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 50, 318\u2013340 (2014).", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva, A. O. et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 40, 631\u2013657 (2021).", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen, G. W. et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 157, 87\u201395 (2017).", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo, J. L. & Nadal, M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 177, 108648\u2013108648 (2019).", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn, E. et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 248, 101\u2013113 (2019).", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai, X. & Son, Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 751, 141622\u2013141622 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li, Y. et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 216, 118295\u2013118295 (2022).", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale, S. E. et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 171, 9\u201318 (2017).", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber, J. L. et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 9, 530\u2013541 (2007).", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -344,28 +344,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9, M. A. et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 55, 5848\u20135856 (2021).", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson, D. T. et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 54, 15768\u201315777 (2020).", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan, J. et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 31, 7\u201326 (2021).", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -379,42 +379,42 @@ { "PMCID": null, "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu, X. C. et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 3, 344\u2013350 (2016).", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -428,21 +428,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka, \u00c1., Szer\u00e9nyi, Z. M., Sz\u00e9chy, A. & Kocsis, T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 48, 126\u2013138 (2013).", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo, J. L. & Adamson, D. T. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 236, 505\u2013513 (2018).", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -507,8 +507,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 16, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -520,14 +520,14 @@ { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -555,63 +555,63 @@ { "PMCID": null, "citation": "Protein Data Bank. the single global archive for 3D macromolecular structure data. Nucleic acids research 47, D520\u2013D528 (2019).", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud, M. et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research 44, D463\u2013D470 (2016).", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma, A. et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics 29, 365\u2013371 (2001).", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -632,21 +632,21 @@ { "PMCID": null, "citation": "Kinkade, D. & Shepherd, A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal 9, 177\u2013186 (2022).", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo, A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science 36, 1059\u20131099 (2022).", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -660,14 +660,14 @@ { "PMCID": null, "citation": "Sicilia, M.-A., Garc\u00eda-Barriocanal, E. & S\u00e1nchez-Alonso, S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science 106, 54\u201360 (2017).", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -681,7 +681,7 @@ { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -695,21 +695,21 @@ { "PMCID": null, "citation": "Thompson, P. T., Powell, C. D. & Moseley, H. N. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one 17, e0277834 (2022).", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -730,14 +730,14 @@ { "PMCID": null, "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -792,8 +792,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 4, + "month": 3, "year": 2023 }, "pubmed_id": null, @@ -812,21 +812,21 @@ { "PMCID": null, "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u201351.", - "doi": "https://doi.org/10.1002/pro.3715", + "doi": "10.1002/pro.3715", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u201351.", - "doi": "https://doi.org/10.1093/nar/gkaa970", + "doi": "10.1093/nar/gkaa970", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", "pubmed_id": null, "title": null }, @@ -847,7 +847,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -868,7 +868,7 @@ { "PMCID": null, "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, @@ -882,14 +882,14 @@ { "PMCID": null, "citation": "Castelli FM. KEGGutils v04.1. Computer software. 2022. Zenodo. https://doi.org/10.5281/zenodo.7482523.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", + "doi": "10.1093/bioinformatics/btp163", "pubmed_id": null, "title": null }, @@ -937,8 +937,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 24, + "month": 7, "year": 2023 }, "pubmed_id": null, @@ -957,35 +957,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u201370.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u20136.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -1027,14 +1027,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. https://doi.org/10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", + "doi": "10.1016/j.cbpa.2016.12.024", "pubmed_id": null, "title": null }, @@ -1048,7 +1048,7 @@ { "PMCID": null, "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", + "doi": "10.1093/gigascience/giab060", "pubmed_id": null, "title": null }, @@ -1062,14 +1062,14 @@ { "PMCID": null, "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u201384.", - "doi": "https://doi.org/10.1107/S0021889809008784", + "doi": "10.1107/S0021889809008784", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u20133.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -1147,7 +1147,7 @@ "methods": null, "publication_date": { "day": null, - "month": null, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -1159,7 +1159,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, @@ -1173,7 +1173,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, @@ -1201,21 +1201,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, @@ -1229,28 +1229,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "doi": "10.1371/journal.pbio.2006930", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", + "doi": "10.1038/nbt.1411", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, @@ -1278,28 +1278,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", + "doi": "10.1038/ng.1054", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", + "doi": "10.1089/omi.2008.0019", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", + "doi": "10.1089/omi.2006.10.164", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", + "doi": "10.4056/sigs.147362", "pubmed_id": null, "title": null }, @@ -1313,35 +1313,35 @@ { "PMCID": null, "citation": "Gamble M Goble C Klyne G Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago Illinois 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", + "doi": "10.1289/EHP10092", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", + "doi": "10.3389/frai.2020.00031", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", + "doi": "10.1093/toxsci/kfm090", "pubmed_id": null, "title": null }, @@ -1369,7 +1369,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", + "doi": "10.1016/j.comtox.2019.100096", "pubmed_id": null, "title": null }, @@ -1383,7 +1383,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", + "doi": "10.1093/nar/gkz1019", "pubmed_id": null, "title": null }, @@ -1397,119 +1397,119 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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"doi": "https://doi.org/10.1186/1471-2105-7-234", + "doi": "10.1186/1471-2105-7-234", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "doi": "10.1021/acs.analchem.9b00748", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "doi": "10.1016/j.ymeth.2004.03.015", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "doi": "10.1002/mas.20108", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "doi": "10.1016/j.aca.2017.04.014", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "doi": "10.1021/ac3018795", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "doi": "10.1021/ac1011574", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "doi": "10.1016/j.pharmthera.2011.12.007", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "doi": "10.1186/1741-7007-9-37", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "doi": "10.1172/JCI72873", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", + "doi": "10.1186/s12859-019-3096-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "doi": "10.3390/metabo10030118", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "doi": "10.1007/s11306-018-1426-9", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", + "doi": "10.3390/metabo10030122", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", + "doi": "10.3390/metabo11110740", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "doi": "10.5936/csbj.201301006", "pubmed_id": null, "title": null }, @@ -1845,21 +1845,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "doi": "10.1021/ac00278a027", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "doi": "10.1371/journal.pcbi.1003118", "pubmed_id": null, "title": null }, @@ -1873,7 +1873,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -1915,7 +1915,7 @@ { "PMCID": null, "citation": null, - 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"doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, @@ -2162,35 +2162,35 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { "PMCID": null, "citation": "Powell, C.D., and Moseley, H.N. (2021). The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites, 11.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C.D., and Moseley, H.N. (2022). The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -2204,7 +2204,7 @@ { "PMCID": null, "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -2246,14 +2246,14 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, diff --git a/tests/testing_files/Crossref_misc.json b/tests/testing_files/Crossref_misc.json index c51acb2..5469c64 100644 --- a/tests/testing_files/Crossref_misc.json +++ b/tests/testing_files/Crossref_misc.json @@ -40,8 +40,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 18, + "month": 11, "year": 2022 }, "pubmed_id": null, @@ -52,7 +52,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", "pubmed_id": null, "title": "PubMed Central: The GenBank of the published literature" }, diff --git a/tests/testing_files/Google_Scholar_merge.json b/tests/testing_files/Google_Scholar_merge.json index 758eeb7..b5bacb7 100644 --- a/tests/testing_files/Google_Scholar_merge.json +++ b/tests/testing_files/Google_Scholar_merge.json @@ -191,8 +191,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 16, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -211,21 +211,21 @@ { "PMCID": null, "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom, A. L. et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS). Sci. Total Envir. 778, 146192 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen, T. et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 1172, 122653 (2021).", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -239,98 +239,98 @@ { "PMCID": null, "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton, S. E. et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 40, 606\u2013630 (2021).", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk, K. H., Darlington, R., Benotti, M., Deeb, R. & Hawley, E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 204, 757\u2013764 (2017).", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. https://doi.org/10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman, M. F., Peldszus, S. & Anderson, W. B. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 50, 318\u2013340 (2014).", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva, A. O. et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 40, 631\u2013657 (2021).", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen, G. W. et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 157, 87\u201395 (2017).", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo, J. L. & Nadal, M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 177, 108648\u2013108648 (2019).", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn, E. et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 248, 101\u2013113 (2019).", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai, X. & Son, Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 751, 141622\u2013141622 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li, Y. et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 216, 118295\u2013118295 (2022).", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale, S. E. et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 171, 9\u201318 (2017).", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber, J. L. et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 9, 530\u2013541 (2007).", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -344,28 +344,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9, M. A. et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 55, 5848\u20135856 (2021).", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson, D. T. et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 54, 15768\u201315777 (2020).", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan, J. et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 31, 7\u201326 (2021).", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -379,42 +379,42 @@ { "PMCID": null, "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu, X. C. et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 3, 344\u2013350 (2016).", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -428,21 +428,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka, \u00c1., Szer\u00e9nyi, Z. M., Sz\u00e9chy, A. & Kocsis, T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 48, 126\u2013138 (2013).", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo, J. L. & Adamson, D. T. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 236, 505\u2013513 (2018).", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -507,8 +507,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 16, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -520,14 +520,14 @@ { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -555,63 +555,63 @@ { "PMCID": null, "citation": "Protein Data Bank. the single global archive for 3D macromolecular structure data. Nucleic acids research 47, D520\u2013D528 (2019).", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud, M. et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research 44, D463\u2013D470 (2016).", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma, A. et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics 29, 365\u2013371 (2001).", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -632,21 +632,21 @@ { "PMCID": null, "citation": "Kinkade, D. & Shepherd, A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal 9, 177\u2013186 (2022).", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo, A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science 36, 1059\u20131099 (2022).", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -660,14 +660,14 @@ { "PMCID": null, "citation": "Sicilia, M.-A., Garc\u00eda-Barriocanal, E. & S\u00e1nchez-Alonso, S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science 106, 54\u201360 (2017).", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -681,7 +681,7 @@ { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -695,21 +695,21 @@ { "PMCID": null, "citation": "Thompson, P. T., Powell, C. D. & Moseley, H. N. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one 17, e0277834 (2022).", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -730,14 +730,14 @@ { "PMCID": null, "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -818,8 +818,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 24, + "month": 7, "year": 2023 }, "pubmed_id": null, @@ -838,35 +838,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u201370.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u20136.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -908,14 +908,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. https://doi.org/10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", + "doi": "10.1016/j.cbpa.2016.12.024", "pubmed_id": null, "title": null }, @@ -929,7 +929,7 @@ { "PMCID": null, "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", + "doi": "10.1093/gigascience/giab060", "pubmed_id": null, "title": null }, @@ -943,14 +943,14 @@ { "PMCID": null, "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u201384.", - "doi": "https://doi.org/10.1107/S0021889809008784", + "doi": "10.1107/S0021889809008784", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u20133.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -1020,7 +1020,7 @@ "methods": null, "publication_date": { "day": null, - "month": null, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -1032,7 +1032,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, @@ -1046,7 +1046,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, @@ -1074,21 +1074,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, @@ -1102,28 +1102,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "doi": "10.1371/journal.pbio.2006930", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", + "doi": "10.1038/nbt.1411", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, @@ -1151,28 +1151,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", + "doi": "10.1038/ng.1054", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", + "doi": "10.1089/omi.2008.0019", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", + "doi": "10.1089/omi.2006.10.164", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", + "doi": "10.4056/sigs.147362", "pubmed_id": null, "title": null }, @@ -1186,35 +1186,35 @@ { "PMCID": null, "citation": "Gamble M Goble C Klyne G Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago Illinois 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", + "doi": "10.1289/EHP10092", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", + "doi": "10.3389/frai.2020.00031", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", + "doi": "10.1093/toxsci/kfm090", "pubmed_id": null, "title": null }, @@ -1242,7 +1242,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", + "doi": "10.1016/j.comtox.2019.100096", "pubmed_id": null, "title": null }, @@ -1256,7 +1256,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", + "doi": "10.1093/nar/gkz1019", "pubmed_id": null, "title": null }, @@ -1270,119 +1270,119 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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"doi": "https://doi.org/10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", "pubmed_id": null, "title": "PubMed Central: The GenBank of the published literature" }, @@ -1551,8 +1551,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 2, + "month": 6, "year": 2022 }, "pubmed_id": null, @@ -1564,147 +1564,147 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "doi": "10.1007/978-1-4939-1258-2_11", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "doi": "10.1186/1471-2105-11-139", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "doi": "10.3390/metabo3040853", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", + "doi": "10.1038/s41374-021-00631-4", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "doi": "10.1186/1471-2105-7-234", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "doi": "10.1021/acs.analchem.9b00748", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "doi": "10.1016/j.ymeth.2004.03.015", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "doi": "10.1002/mas.20108", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "doi": "10.1016/j.aca.2017.04.014", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "doi": "10.1021/ac3018795", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "doi": "10.1021/ac1011574", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "doi": "10.1016/j.pharmthera.2011.12.007", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "doi": "10.1186/1741-7007-9-37", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "doi": "10.1172/JCI72873", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", + "doi": "10.1186/s12859-019-3096-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "doi": "10.3390/metabo10030118", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "doi": "10.1007/s11306-018-1426-9", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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"doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, @@ -2035,35 +2035,35 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { "PMCID": null, "citation": "Powell, C.D., and Moseley, H.N. (2021). The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites, 11.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C.D., and Moseley, H.N. (2022). The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -2077,7 +2077,7 @@ { "PMCID": null, "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -2119,14 +2119,14 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, diff --git a/tests/testing_files/ORCID_merge.json b/tests/testing_files/ORCID_merge.json index bfa97ae..382b0c0 100644 --- a/tests/testing_files/ORCID_merge.json +++ b/tests/testing_files/ORCID_merge.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -220,13 +221,14 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 4, + "month": 11, "year": 2023 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -483,19 +485,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -516,19 +519,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/PubMed_merge.json b/tests/testing_files/PubMed_merge.json index 9e730d6..24af816 100644 --- a/tests/testing_files/PubMed_merge.json +++ b/tests/testing_files/PubMed_merge.json @@ -248,101 +248,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -353,213 +353,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -742,372 +742,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1118,66 +1118,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1257,163 +1257,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1421,76 +1421,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1564,17 +1564,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1595,63 +1595,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1678,21 +1678,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1706,7 +1706,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1725,24 +1725,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1774,16 +1774,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1862,24 +1862,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1918,10 +1918,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1934,15 +1934,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -2012,38 +2012,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2089,10 +2089,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2103,31 +2103,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2216,8 +2216,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2230,14 +2230,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2256,24 +2256,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2284,31 +2284,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2333,31 +2333,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2375,31 +2375,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2412,7 +2412,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2424,24 +2424,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2454,120 +2454,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2578,24 +2578,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2606,10 +2606,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2671,17 +2671,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2801,150 +2801,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2957,22 +2957,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2985,7 +2985,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -3027,7 +3027,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -3055,8 +3055,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -3076,15 +3076,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3269,379 +3269,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3701,35 +3701,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3742,36 +3742,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3826,15 +3826,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/PubMed_modified_to_save_no_PMCID.json b/tests/testing_files/PubMed_modified_to_save_no_PMCID.json index c0009c9..2f864d5 100644 --- a/tests/testing_files/PubMed_modified_to_save_no_PMCID.json +++ b/tests/testing_files/PubMed_modified_to_save_no_PMCID.json @@ -266,7 +266,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1161/circgen.119.002862", + "doi": "10.1161/circgen.119.002862", "grants": [], "journal": "Circulation. Genomic and precision medicine", "keywords": [ diff --git a/tests/testing_files/athr_project_emails_tabular.json b/tests/testing_files/athr_project_emails_tabular.json index 8bdc4ad..3bfe348 100644 --- a/tests/testing_files/athr_project_emails_tabular.json +++ b/tests/testing_files/athr_project_emails_tabular.json @@ -1,9 +1,9 @@ { - "creation_date": "2023-10-02 19:11", + "creation_date": "2023-10-12 15:32", "emails": [ { "attachment": "Col1,Col2\n\"Hunter, Moseley\",Plk1 phosphorylation of PHGDH to regulate serine metabolism\n\"Hunter, Moseley\",Hepatic kinome atlas: An in-depth identification of kinase pathways in liver fibrosis of humans and rodents.\n\"Hunter, Moseley\",Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water.\n", - "attachment_filename": "Core A Administrative Core_Hunter Moseley_project_report.csv", + "attachment_filename": "asdf.csv", "author": "Hunter Moseley", "body": "Attached is the project report for publications found for Core A Administractive Core.\n\nKind regards,\n\nThis email was sent by an automated service. If you have any questions or concerns please email my creator ptth222@uky.edu", "cc": "", diff --git a/tests/testing_files/athr_srch_build_author_loop.txt b/tests/testing_files/athr_srch_build_author_loop.txt index 3ef7842..6960fd2 100644 --- a/tests/testing_files/athr_srch_build_author_loop.txt +++ b/tests/testing_files/athr_srch_build_author_loop.txt @@ -32,7 +32,7 @@ We assiduously mapped kinase pathways using 340 substrate targets, upstream bioi Our findings establish a comprehensive kinase atlas for liver fibrosis, which identifies analogous signaling events conserved among humans and rodents. Conclusions: None Copyrights: © 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases. -DOI: https://doi.org/10.1002/hep.32467 +DOI: 10.1002/hep.32467 Journal: Hepatology (Baltimore, Md.) Keywords: [] Methods: None @@ -357,7 +357,7 @@ Grants: P42 ES007380, 2020026 Abstract: Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps. Conclusions: None Copyrights: © 2023. The Author(s). -DOI: https://doi.org/10.1038/s41597-023-02277-x +DOI: 10.1038/s41597-023-02277-x Journal: Scientific data Keywords: [] Methods: None @@ -395,19 +395,19 @@ Citation: Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.mex.2020.101111 +DOI: 10.1016/j.mex.2020.101111 Citation: Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2021.146192 +DOI: 10.1016/j.scitotenv.2021.146192 Citation: Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jchromb.2021.122653 +DOI: 10.1016/j.jchromb.2021.122653 Citation: Glüge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345–2373. Title: None @@ -419,85 +419,85 @@ Citation: Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substa Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41370-021-00316-6 +DOI: 10.1038/s41370-021-00316-6 Citation: Haukås M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360–371. doi: 10.1016/j.envpol.2006.09.021. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2006.09.021 +DOI: 10.1016/j.envpol.2006.09.021 Citation: Fenton SE, et al. Per‐and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606–630. doi: 10.1002/etc.4890. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4890 +DOI: 10.1002/etc.4890 Citation: Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757–764. doi: 10.1016/j.jenvman.2017.08.016. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jenvman.2017.08.016 +DOI: 10.1016/j.jenvman.2017.08.016 Citation: National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022). Title: None PMID: None PMCID: None -DOI: https://doi.org/10.17226/26156 +DOI: 10.17226/26156 Citation: Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318–340. doi: 10.1016/j.watres.2013.10.045. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2013.10.045 +DOI: 10.1016/j.watres.2013.10.045 Citation: De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631–657. doi: 10.1002/etc.4935. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4935 +DOI: 10.1002/etc.4935 Citation: Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000–2015. Environ. Res. 2017;157:87–95. doi: 10.1016/j.envres.2017.05.013. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2017.05.013 +DOI: 10.1016/j.envres.2017.05.013 Citation: Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648–108648. doi: 10.1016/j.envres.2019.108648. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2019.108648 +DOI: 10.1016/j.envres.2019.108648 Citation: Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101–113. doi: 10.1016/j.envpol.2019.02.018. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2019.02.018 +DOI: 10.1016/j.envpol.2019.02.018 Citation: Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622–141622. doi: 10.1016/j.scitotenv.2020.141622. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2020.141622 +DOI: 10.1016/j.scitotenv.2020.141622 Citation: Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295–118295. doi: 10.1016/j.watres.2022.118295. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2022.118295 +DOI: 10.1016/j.watres.2022.118295 Citation: Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9–18. doi: 10.1016/j.chemosphere.2016.12.057. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2016.12.057 +DOI: 10.1016/j.chemosphere.2016.12.057 Citation: Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530–541. doi: 10.1039/b701417a. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1039/b701417a +DOI: 10.1039/b701417a Citation: Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887–1898. Title: None @@ -509,25 +509,25 @@ Citation: Pétré MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c07978 +DOI: 10.1021/acs.est.0c07978 Citation: Ahrens L, Norström K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33–38. doi: 10.1016/j.chemosphere.2014.03.136. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2014.03.136 +DOI: 10.1016/j.chemosphere.2014.03.136 Citation: Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768–15777. doi: 10.1021/acs.est.0c04472. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c04472 +DOI: 10.1021/acs.est.0c04472 Citation: Quinnan J, et al. Application of PFAS‐mobile lab to support adaptive characterization and flux‐based conceptual site models at AFFF releases. Remed. J. 2021;31:7–26. doi: 10.1002/rem.21680. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/rem.21680 +DOI: 10.1002/rem.21680 Citation: Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291–301. Title: None @@ -539,37 +539,37 @@ Citation: Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3389/fenvs.2021.796026 +DOI: 10.3389/fenvs.2021.796026 Citation: Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344–350. doi: 10.1021/acs.estlett.6b00260. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.estlett.6b00260 +DOI: 10.1021/acs.estlett.6b00260 Citation: Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per‐and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163–174. doi: 10.1002/ieam.4614. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/ieam.4614 +DOI: 10.1002/ieam.4614 Citation: Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54–65. doi: 10.1110/ps.073138508. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1110/ps.073138508 +DOI: 10.1110/ps.073138508 Citation: Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1–9. doi: 10.1038/sdata.2016.18. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2016.18 +DOI: 10.1038/sdata.2016.18 Citation: Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931–936. doi: 10.1038/s41431-018-0160-0. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41431-018-0160-0 +DOI: 10.1038/s41431-018-0160-0 Citation: Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023). Title: None @@ -581,17 +581,17 @@ Citation: Zsóka Á, Szerényi ZM, Széchy A, Kocsis T. Greening due to environm Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jclepro.2012.11.030 +DOI: 10.1016/j.jclepro.2012.11.030 Citation: Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505–513. doi: 10.1016/j.envpol.2018.01.066. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2018.01.066 +DOI: 10.1016/j.envpol.2018.01.066 Citation: Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.6084/m9.figshare.15218958 +DOI: 10.6084/m9.figshare.15218958 diff --git a/tests/testing_files/athr_srch_summary_report.txt b/tests/testing_files/athr_srch_summary_report.txt index 808b5e0..79f45a9 100644 --- a/tests/testing_files/athr_srch_summary_report.txt +++ b/tests/testing_files/athr_srch_summary_report.txt @@ -11,7 +11,7 @@ Core A Administrative Core Title: Hepatic kinome atlas: An in-depth identification of kinase pathways in liver fibrosis of humans and rodents. Authors: Justin F Creeden, Zachary A Kipp, Mei Xu, Robert M Flight, Hunter N B Moseley, Genesee J Martinez, Wang-Hsin Lee, Khaled Alganem, Ali S Imami, Megan R McMullen, Sanjoy Roychowdhury, Atta M Nawabi, Jennifer A Hipp, Samir Softic, Steven A Weinman, Robert McCullumsmith, Laura E Nagy, Terry D Hinds Journal: Hepatology (Baltimore, Md.) - DOI: https://doi.org/10.1002/hep.32467 + DOI: 10.1002/hep.32467 PMID: 35313030 PMCID: PMC9489820 Grants: R01 MH121102, R01 AG057598, R01 DK121797, R01 MH107487, P30 CA177558, P50 AA024333 @@ -19,7 +19,7 @@ Core A Administrative Core Title: Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Authors: Sweta Ojha, P Travis Thompson, Christian D Powell, Hunter N B Moseley, Kelly G Pennell Journal: Scientific data - DOI: https://doi.org/10.1038/s41597-023-02277-x + DOI: 10.1038/s41597-023-02277-x PMID: 37328532 PMCID: PMC10275912 Grants: P42 ES007380, 2020026 @@ -37,7 +37,7 @@ Project 1 Title: Hepatic kinome atlas: An in-depth identification of kinase pathways in liver fibrosis of humans and rodents. Authors: Justin F Creeden, Zachary A Kipp, Mei Xu, Robert M Flight, Hunter N B Moseley, Genesee J Martinez, Wang-Hsin Lee, Khaled Alganem, Ali S Imami, Megan R McMullen, Sanjoy Roychowdhury, Atta M Nawabi, Jennifer A Hipp, Samir Softic, Steven A Weinman, Robert McCullumsmith, Laura E Nagy, Terry D Hinds Journal: Hepatology (Baltimore, Md.) - DOI: https://doi.org/10.1002/hep.32467 + DOI: 10.1002/hep.32467 PMID: 35313030 PMCID: PMC9489820 Grants: R01 MH121102, R01 AG057598, R01 DK121797, R01 MH107487, P30 CA177558, P50 AA024333 @@ -45,7 +45,7 @@ Project 1 Title: Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Authors: Sweta Ojha, P Travis Thompson, Christian D Powell, Hunter N B Moseley, Kelly G Pennell Journal: Scientific data - DOI: https://doi.org/10.1038/s41597-023-02277-x + DOI: 10.1038/s41597-023-02277-x PMID: 37328532 PMCID: PMC10275912 Grants: P42 ES007380, 2020026 @@ -63,7 +63,7 @@ No Project Report Title: Hepatic kinome atlas: An in-depth identification of kinase pathways in liver fibrosis of humans and rodents. Authors: Justin F Creeden, Zachary A Kipp, Mei Xu, Robert M Flight, Hunter N B Moseley, Genesee J Martinez, Wang-Hsin Lee, Khaled Alganem, Ali S Imami, Megan R McMullen, Sanjoy Roychowdhury, Atta M Nawabi, Jennifer A Hipp, Samir Softic, Steven A Weinman, Robert McCullumsmith, Laura E Nagy, Terry D Hinds Journal: Hepatology (Baltimore, Md.) - DOI: https://doi.org/10.1002/hep.32467 + DOI: 10.1002/hep.32467 PMID: 35313030 PMCID: PMC9489820 Grants: R01 MH121102, R01 AG057598, R01 DK121797, R01 MH107487, P30 CA177558, P50 AA024333 @@ -71,7 +71,7 @@ No Project Report Title: Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Authors: Sweta Ojha, P Travis Thompson, Christian D Powell, Hunter N B Moseley, Kelly G Pennell Journal: Scientific data - DOI: https://doi.org/10.1038/s41597-023-02277-x + DOI: 10.1038/s41597-023-02277-x PMID: 37328532 PMCID: PMC10275912 Grants: P42 ES007380, 2020026 @@ -89,7 +89,7 @@ No Authors Title: Hepatic kinome atlas: An in-depth identification of kinase pathways in liver fibrosis of humans and rodents. Authors: Justin F Creeden, Zachary A Kipp, Mei Xu, Robert M Flight, Hunter N B Moseley, Genesee J Martinez, Wang-Hsin Lee, Khaled Alganem, Ali S Imami, Megan R McMullen, Sanjoy Roychowdhury, Atta M Nawabi, Jennifer A Hipp, Samir Softic, Steven A Weinman, Robert McCullumsmith, Laura E Nagy, Terry D Hinds Journal: Hepatology (Baltimore, Md.) - DOI: https://doi.org/10.1002/hep.32467 + DOI: 10.1002/hep.32467 PMID: 35313030 PMCID: PMC9489820 Grants: R01 MH121102, R01 AG057598, R01 DK121797, R01 MH107487, P30 CA177558, P50 AA024333 @@ -97,7 +97,7 @@ No Authors Title: Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Authors: Sweta Ojha, P Travis Thompson, Christian D Powell, Hunter N B Moseley, Kelly G Pennell Journal: Scientific data - DOI: https://doi.org/10.1038/s41597-023-02277-x + DOI: 10.1038/s41597-023-02277-x PMID: 37328532 PMCID: PMC10275912 Grants: P42 ES007380, 2020026 @@ -106,7 +106,7 @@ No Authors Title: Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Authors: Sweta Ojha, P Travis Thompson, Christian D Powell, Hunter N B Moseley, Kelly G Pennell Journal: Scientific data - DOI: https://doi.org/10.1038/s41597-023-02277-x + DOI: 10.1038/s41597-023-02277-x PMID: 37328532 PMCID: PMC10275912 Grants: P42 ES007380, 2020026 @@ -124,7 +124,7 @@ No from_email Title: Hepatic kinome atlas: An in-depth identification of kinase pathways in liver fibrosis of humans and rodents. Authors: Justin F Creeden, Zachary A Kipp, Mei Xu, Robert M Flight, Hunter N B Moseley, Genesee J Martinez, Wang-Hsin Lee, Khaled Alganem, Ali S Imami, Megan R McMullen, Sanjoy Roychowdhury, Atta M Nawabi, Jennifer A Hipp, Samir Softic, Steven A Weinman, Robert McCullumsmith, Laura E Nagy, Terry D Hinds Journal: Hepatology (Baltimore, Md.) - DOI: https://doi.org/10.1002/hep.32467 + DOI: 10.1002/hep.32467 PMID: 35313030 PMCID: PMC9489820 Grants: R01 MH121102, R01 AG057598, R01 DK121797, R01 MH107487, P30 CA177558, P50 AA024333 @@ -132,7 +132,7 @@ No from_email Title: Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Authors: Sweta Ojha, P Travis Thompson, Christian D Powell, Hunter N B Moseley, Kelly G Pennell Journal: Scientific data - DOI: https://doi.org/10.1038/s41597-023-02277-x + DOI: 10.1038/s41597-023-02277-x PMID: 37328532 PMCID: PMC10275912 Grants: P42 ES007380, 2020026 @@ -141,7 +141,7 @@ No from_email Title: Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Authors: Sweta Ojha, P Travis Thompson, Christian D Powell, Hunter N B Moseley, Kelly G Pennell Journal: Scientific data - DOI: https://doi.org/10.1038/s41597-023-02277-x + DOI: 10.1038/s41597-023-02277-x PMID: 37328532 PMCID: PMC10275912 Grants: P42 ES007380, 2020026 diff --git a/tests/testing_files/athr_srch_summary_report_custom_template.txt b/tests/testing_files/athr_srch_summary_report_custom_template.txt index e5d9b02..362320a 100644 --- a/tests/testing_files/athr_srch_summary_report_custom_template.txt +++ b/tests/testing_files/athr_srch_summary_report_custom_template.txt @@ -32,7 +32,7 @@ We assiduously mapped kinase pathways using 340 substrate targets, upstream bioi Our findings establish a comprehensive kinase atlas for liver fibrosis, which identifies analogous signaling events conserved among humans and rodents. Conclusions: None Copyrights: © 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases. -DOI: https://doi.org/10.1002/hep.32467 +DOI: 10.1002/hep.32467 Journal: Hepatology (Baltimore, Md.) Keywords: [] Methods: None @@ -357,7 +357,7 @@ Grants: P42 ES007380, 2020026 Abstract: Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps. Conclusions: None Copyrights: © 2023. The Author(s). -DOI: https://doi.org/10.1038/s41597-023-02277-x +DOI: 10.1038/s41597-023-02277-x Journal: Scientific data Keywords: [] Methods: None @@ -395,19 +395,19 @@ Citation: Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.mex.2020.101111 +DOI: 10.1016/j.mex.2020.101111 Citation: Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2021.146192 +DOI: 10.1016/j.scitotenv.2021.146192 Citation: Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jchromb.2021.122653 +DOI: 10.1016/j.jchromb.2021.122653 Citation: Glüge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345–2373. Title: None @@ -419,85 +419,85 @@ Citation: Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substa Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41370-021-00316-6 +DOI: 10.1038/s41370-021-00316-6 Citation: Haukås M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360–371. doi: 10.1016/j.envpol.2006.09.021. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2006.09.021 +DOI: 10.1016/j.envpol.2006.09.021 Citation: Fenton SE, et al. Per‐and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606–630. doi: 10.1002/etc.4890. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4890 +DOI: 10.1002/etc.4890 Citation: Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757–764. doi: 10.1016/j.jenvman.2017.08.016. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jenvman.2017.08.016 +DOI: 10.1016/j.jenvman.2017.08.016 Citation: National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022). Title: None PMID: None PMCID: None -DOI: https://doi.org/10.17226/26156 +DOI: 10.17226/26156 Citation: Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318–340. doi: 10.1016/j.watres.2013.10.045. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2013.10.045 +DOI: 10.1016/j.watres.2013.10.045 Citation: De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631–657. doi: 10.1002/etc.4935. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4935 +DOI: 10.1002/etc.4935 Citation: Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000–2015. Environ. Res. 2017;157:87–95. doi: 10.1016/j.envres.2017.05.013. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2017.05.013 +DOI: 10.1016/j.envres.2017.05.013 Citation: Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648–108648. doi: 10.1016/j.envres.2019.108648. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2019.108648 +DOI: 10.1016/j.envres.2019.108648 Citation: Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101–113. doi: 10.1016/j.envpol.2019.02.018. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2019.02.018 +DOI: 10.1016/j.envpol.2019.02.018 Citation: Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622–141622. doi: 10.1016/j.scitotenv.2020.141622. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2020.141622 +DOI: 10.1016/j.scitotenv.2020.141622 Citation: Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295–118295. doi: 10.1016/j.watres.2022.118295. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2022.118295 +DOI: 10.1016/j.watres.2022.118295 Citation: Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9–18. doi: 10.1016/j.chemosphere.2016.12.057. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2016.12.057 +DOI: 10.1016/j.chemosphere.2016.12.057 Citation: Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530–541. doi: 10.1039/b701417a. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1039/b701417a +DOI: 10.1039/b701417a Citation: Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887–1898. Title: None @@ -509,25 +509,25 @@ Citation: Pétré MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c07978 +DOI: 10.1021/acs.est.0c07978 Citation: Ahrens L, Norström K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33–38. doi: 10.1016/j.chemosphere.2014.03.136. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2014.03.136 +DOI: 10.1016/j.chemosphere.2014.03.136 Citation: Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768–15777. doi: 10.1021/acs.est.0c04472. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c04472 +DOI: 10.1021/acs.est.0c04472 Citation: Quinnan J, et al. Application of PFAS‐mobile lab to support adaptive characterization and flux‐based conceptual site models at AFFF releases. Remed. J. 2021;31:7–26. doi: 10.1002/rem.21680. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/rem.21680 +DOI: 10.1002/rem.21680 Citation: Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291–301. Title: None @@ -539,37 +539,37 @@ Citation: Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3389/fenvs.2021.796026 +DOI: 10.3389/fenvs.2021.796026 Citation: Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344–350. doi: 10.1021/acs.estlett.6b00260. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.estlett.6b00260 +DOI: 10.1021/acs.estlett.6b00260 Citation: Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per‐and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163–174. doi: 10.1002/ieam.4614. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/ieam.4614 +DOI: 10.1002/ieam.4614 Citation: Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54–65. doi: 10.1110/ps.073138508. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1110/ps.073138508 +DOI: 10.1110/ps.073138508 Citation: Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1–9. doi: 10.1038/sdata.2016.18. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2016.18 +DOI: 10.1038/sdata.2016.18 Citation: Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931–936. doi: 10.1038/s41431-018-0160-0. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41431-018-0160-0 +DOI: 10.1038/s41431-018-0160-0 Citation: Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023). Title: None @@ -581,19 +581,19 @@ Citation: Zsóka Á, Szerényi ZM, Széchy A, Kocsis T. Greening due to environm Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jclepro.2012.11.030 +DOI: 10.1016/j.jclepro.2012.11.030 Citation: Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505–513. doi: 10.1016/j.envpol.2018.01.066. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2018.01.066 +DOI: 10.1016/j.envpol.2018.01.066 Citation: Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.6084/m9.figshare.15218958 +DOI: 10.6084/m9.figshare.15218958 Authors: Hunter Moseley @@ -629,7 +629,7 @@ We assiduously mapped kinase pathways using 340 substrate targets, upstream bioi Our findings establish a comprehensive kinase atlas for liver fibrosis, which identifies analogous signaling events conserved among humans and rodents. Conclusions: None Copyrights: © 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases. -DOI: https://doi.org/10.1002/hep.32467 +DOI: 10.1002/hep.32467 Journal: Hepatology (Baltimore, Md.) Keywords: [] Methods: None @@ -954,7 +954,7 @@ Grants: P42 ES007380, 2020026 Abstract: Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps. Conclusions: None Copyrights: © 2023. The Author(s). -DOI: https://doi.org/10.1038/s41597-023-02277-x +DOI: 10.1038/s41597-023-02277-x Journal: Scientific data Keywords: [] Methods: None @@ -992,19 +992,19 @@ Citation: Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.mex.2020.101111 +DOI: 10.1016/j.mex.2020.101111 Citation: Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2021.146192 +DOI: 10.1016/j.scitotenv.2021.146192 Citation: Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jchromb.2021.122653 +DOI: 10.1016/j.jchromb.2021.122653 Citation: Glüge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345–2373. Title: None @@ -1016,85 +1016,85 @@ Citation: Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substa Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41370-021-00316-6 +DOI: 10.1038/s41370-021-00316-6 Citation: Haukås M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360–371. doi: 10.1016/j.envpol.2006.09.021. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2006.09.021 +DOI: 10.1016/j.envpol.2006.09.021 Citation: Fenton SE, et al. Per‐and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606–630. doi: 10.1002/etc.4890. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4890 +DOI: 10.1002/etc.4890 Citation: Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757–764. doi: 10.1016/j.jenvman.2017.08.016. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jenvman.2017.08.016 +DOI: 10.1016/j.jenvman.2017.08.016 Citation: National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022). Title: None PMID: None PMCID: None -DOI: https://doi.org/10.17226/26156 +DOI: 10.17226/26156 Citation: Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318–340. doi: 10.1016/j.watres.2013.10.045. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2013.10.045 +DOI: 10.1016/j.watres.2013.10.045 Citation: De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631–657. doi: 10.1002/etc.4935. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4935 +DOI: 10.1002/etc.4935 Citation: Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000–2015. Environ. Res. 2017;157:87–95. doi: 10.1016/j.envres.2017.05.013. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2017.05.013 +DOI: 10.1016/j.envres.2017.05.013 Citation: Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648–108648. doi: 10.1016/j.envres.2019.108648. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2019.108648 +DOI: 10.1016/j.envres.2019.108648 Citation: Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101–113. doi: 10.1016/j.envpol.2019.02.018. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2019.02.018 +DOI: 10.1016/j.envpol.2019.02.018 Citation: Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622–141622. doi: 10.1016/j.scitotenv.2020.141622. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2020.141622 +DOI: 10.1016/j.scitotenv.2020.141622 Citation: Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295–118295. doi: 10.1016/j.watres.2022.118295. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2022.118295 +DOI: 10.1016/j.watres.2022.118295 Citation: Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9–18. doi: 10.1016/j.chemosphere.2016.12.057. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2016.12.057 +DOI: 10.1016/j.chemosphere.2016.12.057 Citation: Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530–541. doi: 10.1039/b701417a. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1039/b701417a +DOI: 10.1039/b701417a Citation: Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887–1898. Title: None @@ -1106,25 +1106,25 @@ Citation: Pétré MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c07978 +DOI: 10.1021/acs.est.0c07978 Citation: Ahrens L, Norström K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33–38. doi: 10.1016/j.chemosphere.2014.03.136. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2014.03.136 +DOI: 10.1016/j.chemosphere.2014.03.136 Citation: Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768–15777. doi: 10.1021/acs.est.0c04472. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c04472 +DOI: 10.1021/acs.est.0c04472 Citation: Quinnan J, et al. Application of PFAS‐mobile lab to support adaptive characterization and flux‐based conceptual site models at AFFF releases. Remed. J. 2021;31:7–26. doi: 10.1002/rem.21680. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/rem.21680 +DOI: 10.1002/rem.21680 Citation: Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291–301. Title: None @@ -1136,37 +1136,37 @@ Citation: Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3389/fenvs.2021.796026 +DOI: 10.3389/fenvs.2021.796026 Citation: Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344–350. doi: 10.1021/acs.estlett.6b00260. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.estlett.6b00260 +DOI: 10.1021/acs.estlett.6b00260 Citation: Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per‐and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163–174. doi: 10.1002/ieam.4614. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/ieam.4614 +DOI: 10.1002/ieam.4614 Citation: Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54–65. doi: 10.1110/ps.073138508. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1110/ps.073138508 +DOI: 10.1110/ps.073138508 Citation: Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1–9. doi: 10.1038/sdata.2016.18. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2016.18 +DOI: 10.1038/sdata.2016.18 Citation: Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931–936. doi: 10.1038/s41431-018-0160-0. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41431-018-0160-0 +DOI: 10.1038/s41431-018-0160-0 Citation: Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023). Title: None @@ -1178,19 +1178,19 @@ Citation: Zsóka Á, Szerényi ZM, Széchy A, Kocsis T. Greening due to environm Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jclepro.2012.11.030 +DOI: 10.1016/j.jclepro.2012.11.030 Citation: Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505–513. doi: 10.1016/j.envpol.2018.01.066. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2018.01.066 +DOI: 10.1016/j.envpol.2018.01.066 Citation: Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.6084/m9.figshare.15218958 +DOI: 10.6084/m9.figshare.15218958 Authors: Hunter Moseley @@ -1226,7 +1226,7 @@ We assiduously mapped kinase pathways using 340 substrate targets, upstream bioi Our findings establish a comprehensive kinase atlas for liver fibrosis, which identifies analogous signaling events conserved among humans and rodents. Conclusions: None Copyrights: © 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases. -DOI: https://doi.org/10.1002/hep.32467 +DOI: 10.1002/hep.32467 Journal: Hepatology (Baltimore, Md.) Keywords: [] Methods: None @@ -1551,7 +1551,7 @@ Grants: P42 ES007380, 2020026 Abstract: Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps. Conclusions: None Copyrights: © 2023. The Author(s). -DOI: https://doi.org/10.1038/s41597-023-02277-x +DOI: 10.1038/s41597-023-02277-x Journal: Scientific data Keywords: [] Methods: None @@ -1589,19 +1589,19 @@ Citation: Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.mex.2020.101111 +DOI: 10.1016/j.mex.2020.101111 Citation: Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2021.146192 +DOI: 10.1016/j.scitotenv.2021.146192 Citation: Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jchromb.2021.122653 +DOI: 10.1016/j.jchromb.2021.122653 Citation: Glüge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345–2373. Title: None @@ -1613,85 +1613,85 @@ Citation: Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substa Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41370-021-00316-6 +DOI: 10.1038/s41370-021-00316-6 Citation: Haukås M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360–371. doi: 10.1016/j.envpol.2006.09.021. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2006.09.021 +DOI: 10.1016/j.envpol.2006.09.021 Citation: Fenton SE, et al. Per‐and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606–630. doi: 10.1002/etc.4890. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4890 +DOI: 10.1002/etc.4890 Citation: Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757–764. doi: 10.1016/j.jenvman.2017.08.016. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jenvman.2017.08.016 +DOI: 10.1016/j.jenvman.2017.08.016 Citation: National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022). Title: None PMID: None PMCID: None -DOI: https://doi.org/10.17226/26156 +DOI: 10.17226/26156 Citation: Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318–340. doi: 10.1016/j.watres.2013.10.045. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2013.10.045 +DOI: 10.1016/j.watres.2013.10.045 Citation: De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631–657. doi: 10.1002/etc.4935. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4935 +DOI: 10.1002/etc.4935 Citation: Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000–2015. Environ. Res. 2017;157:87–95. doi: 10.1016/j.envres.2017.05.013. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2017.05.013 +DOI: 10.1016/j.envres.2017.05.013 Citation: Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648–108648. doi: 10.1016/j.envres.2019.108648. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2019.108648 +DOI: 10.1016/j.envres.2019.108648 Citation: Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101–113. doi: 10.1016/j.envpol.2019.02.018. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2019.02.018 +DOI: 10.1016/j.envpol.2019.02.018 Citation: Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622–141622. doi: 10.1016/j.scitotenv.2020.141622. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2020.141622 +DOI: 10.1016/j.scitotenv.2020.141622 Citation: Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295–118295. doi: 10.1016/j.watres.2022.118295. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2022.118295 +DOI: 10.1016/j.watres.2022.118295 Citation: Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9–18. doi: 10.1016/j.chemosphere.2016.12.057. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2016.12.057 +DOI: 10.1016/j.chemosphere.2016.12.057 Citation: Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530–541. doi: 10.1039/b701417a. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1039/b701417a +DOI: 10.1039/b701417a Citation: Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887–1898. Title: None @@ -1703,25 +1703,25 @@ Citation: Pétré MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c07978 +DOI: 10.1021/acs.est.0c07978 Citation: Ahrens L, Norström K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33–38. doi: 10.1016/j.chemosphere.2014.03.136. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2014.03.136 +DOI: 10.1016/j.chemosphere.2014.03.136 Citation: Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768–15777. doi: 10.1021/acs.est.0c04472. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c04472 +DOI: 10.1021/acs.est.0c04472 Citation: Quinnan J, et al. Application of PFAS‐mobile lab to support adaptive characterization and flux‐based conceptual site models at AFFF releases. Remed. J. 2021;31:7–26. doi: 10.1002/rem.21680. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/rem.21680 +DOI: 10.1002/rem.21680 Citation: Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291–301. Title: None @@ -1733,37 +1733,37 @@ Citation: Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3389/fenvs.2021.796026 +DOI: 10.3389/fenvs.2021.796026 Citation: Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344–350. doi: 10.1021/acs.estlett.6b00260. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.estlett.6b00260 +DOI: 10.1021/acs.estlett.6b00260 Citation: Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per‐and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163–174. doi: 10.1002/ieam.4614. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/ieam.4614 +DOI: 10.1002/ieam.4614 Citation: Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54–65. doi: 10.1110/ps.073138508. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1110/ps.073138508 +DOI: 10.1110/ps.073138508 Citation: Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1–9. doi: 10.1038/sdata.2016.18. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2016.18 +DOI: 10.1038/sdata.2016.18 Citation: Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931–936. doi: 10.1038/s41431-018-0160-0. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41431-018-0160-0 +DOI: 10.1038/s41431-018-0160-0 Citation: Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023). Title: None @@ -1775,19 +1775,19 @@ Citation: Zsóka Á, Szerényi ZM, Széchy A, Kocsis T. Greening due to environm Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jclepro.2012.11.030 +DOI: 10.1016/j.jclepro.2012.11.030 Citation: Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505–513. doi: 10.1016/j.envpol.2018.01.066. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2018.01.066 +DOI: 10.1016/j.envpol.2018.01.066 Citation: Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.6084/m9.figshare.15218958 +DOI: 10.6084/m9.figshare.15218958 Authors: Hunter Moseley @@ -1823,7 +1823,7 @@ We assiduously mapped kinase pathways using 340 substrate targets, upstream bioi Our findings establish a comprehensive kinase atlas for liver fibrosis, which identifies analogous signaling events conserved among humans and rodents. Conclusions: None Copyrights: © 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases. -DOI: https://doi.org/10.1002/hep.32467 +DOI: 10.1002/hep.32467 Journal: Hepatology (Baltimore, Md.) Keywords: [] Methods: None @@ -2148,7 +2148,7 @@ Grants: P42 ES007380, 2020026 Abstract: Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps. Conclusions: None Copyrights: © 2023. The Author(s). -DOI: https://doi.org/10.1038/s41597-023-02277-x +DOI: 10.1038/s41597-023-02277-x Journal: Scientific data Keywords: [] Methods: None @@ -2186,19 +2186,19 @@ Citation: Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.mex.2020.101111 +DOI: 10.1016/j.mex.2020.101111 Citation: Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2021.146192 +DOI: 10.1016/j.scitotenv.2021.146192 Citation: Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jchromb.2021.122653 +DOI: 10.1016/j.jchromb.2021.122653 Citation: Glüge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345–2373. Title: None @@ -2210,85 +2210,85 @@ Citation: Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substa Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41370-021-00316-6 +DOI: 10.1038/s41370-021-00316-6 Citation: Haukås M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360–371. doi: 10.1016/j.envpol.2006.09.021. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2006.09.021 +DOI: 10.1016/j.envpol.2006.09.021 Citation: Fenton SE, et al. Per‐and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606–630. doi: 10.1002/etc.4890. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4890 +DOI: 10.1002/etc.4890 Citation: Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757–764. doi: 10.1016/j.jenvman.2017.08.016. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jenvman.2017.08.016 +DOI: 10.1016/j.jenvman.2017.08.016 Citation: National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022). Title: None PMID: None PMCID: None -DOI: https://doi.org/10.17226/26156 +DOI: 10.17226/26156 Citation: Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318–340. doi: 10.1016/j.watres.2013.10.045. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2013.10.045 +DOI: 10.1016/j.watres.2013.10.045 Citation: De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631–657. doi: 10.1002/etc.4935. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4935 +DOI: 10.1002/etc.4935 Citation: Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000–2015. Environ. Res. 2017;157:87–95. doi: 10.1016/j.envres.2017.05.013. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2017.05.013 +DOI: 10.1016/j.envres.2017.05.013 Citation: Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648–108648. doi: 10.1016/j.envres.2019.108648. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2019.108648 +DOI: 10.1016/j.envres.2019.108648 Citation: Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101–113. doi: 10.1016/j.envpol.2019.02.018. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2019.02.018 +DOI: 10.1016/j.envpol.2019.02.018 Citation: Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622–141622. doi: 10.1016/j.scitotenv.2020.141622. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2020.141622 +DOI: 10.1016/j.scitotenv.2020.141622 Citation: Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295–118295. doi: 10.1016/j.watres.2022.118295. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2022.118295 +DOI: 10.1016/j.watres.2022.118295 Citation: Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9–18. doi: 10.1016/j.chemosphere.2016.12.057. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2016.12.057 +DOI: 10.1016/j.chemosphere.2016.12.057 Citation: Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530–541. doi: 10.1039/b701417a. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1039/b701417a +DOI: 10.1039/b701417a Citation: Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887–1898. Title: None @@ -2300,25 +2300,25 @@ Citation: Pétré MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c07978 +DOI: 10.1021/acs.est.0c07978 Citation: Ahrens L, Norström K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33–38. doi: 10.1016/j.chemosphere.2014.03.136. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2014.03.136 +DOI: 10.1016/j.chemosphere.2014.03.136 Citation: Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768–15777. doi: 10.1021/acs.est.0c04472. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c04472 +DOI: 10.1021/acs.est.0c04472 Citation: Quinnan J, et al. Application of PFAS‐mobile lab to support adaptive characterization and flux‐based conceptual site models at AFFF releases. Remed. J. 2021;31:7–26. doi: 10.1002/rem.21680. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/rem.21680 +DOI: 10.1002/rem.21680 Citation: Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291–301. Title: None @@ -2330,37 +2330,37 @@ Citation: Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3389/fenvs.2021.796026 +DOI: 10.3389/fenvs.2021.796026 Citation: Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344–350. doi: 10.1021/acs.estlett.6b00260. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.estlett.6b00260 +DOI: 10.1021/acs.estlett.6b00260 Citation: Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per‐and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163–174. doi: 10.1002/ieam.4614. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/ieam.4614 +DOI: 10.1002/ieam.4614 Citation: Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54–65. doi: 10.1110/ps.073138508. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1110/ps.073138508 +DOI: 10.1110/ps.073138508 Citation: Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1–9. doi: 10.1038/sdata.2016.18. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2016.18 +DOI: 10.1038/sdata.2016.18 Citation: Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931–936. doi: 10.1038/s41431-018-0160-0. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41431-018-0160-0 +DOI: 10.1038/s41431-018-0160-0 Citation: Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023). Title: None @@ -2372,19 +2372,19 @@ Citation: Zsóka Á, Szerényi ZM, Széchy A, Kocsis T. Greening due to environm Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jclepro.2012.11.030 +DOI: 10.1016/j.jclepro.2012.11.030 Citation: Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505–513. doi: 10.1016/j.envpol.2018.01.066. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2018.01.066 +DOI: 10.1016/j.envpol.2018.01.066 Citation: Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.6084/m9.figshare.15218958 +DOI: 10.6084/m9.figshare.15218958 Authors: Hunter Moseley @@ -2420,7 +2420,7 @@ We assiduously mapped kinase pathways using 340 substrate targets, upstream bioi Our findings establish a comprehensive kinase atlas for liver fibrosis, which identifies analogous signaling events conserved among humans and rodents. Conclusions: None Copyrights: © 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases. -DOI: https://doi.org/10.1002/hep.32467 +DOI: 10.1002/hep.32467 Journal: Hepatology (Baltimore, Md.) Keywords: [] Methods: None @@ -2745,7 +2745,7 @@ Grants: P42 ES007380, 2020026 Abstract: Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps. Conclusions: None Copyrights: © 2023. The Author(s). -DOI: https://doi.org/10.1038/s41597-023-02277-x +DOI: 10.1038/s41597-023-02277-x Journal: Scientific data Keywords: [] Methods: None @@ -2783,19 +2783,19 @@ Citation: Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.mex.2020.101111 +DOI: 10.1016/j.mex.2020.101111 Citation: Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2021.146192 +DOI: 10.1016/j.scitotenv.2021.146192 Citation: Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jchromb.2021.122653 +DOI: 10.1016/j.jchromb.2021.122653 Citation: Glüge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345–2373. Title: None @@ -2807,85 +2807,85 @@ Citation: Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substa Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41370-021-00316-6 +DOI: 10.1038/s41370-021-00316-6 Citation: Haukås M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360–371. doi: 10.1016/j.envpol.2006.09.021. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2006.09.021 +DOI: 10.1016/j.envpol.2006.09.021 Citation: Fenton SE, et al. Per‐and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606–630. doi: 10.1002/etc.4890. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4890 +DOI: 10.1002/etc.4890 Citation: Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757–764. doi: 10.1016/j.jenvman.2017.08.016. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jenvman.2017.08.016 +DOI: 10.1016/j.jenvman.2017.08.016 Citation: National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022). Title: None PMID: None PMCID: None -DOI: https://doi.org/10.17226/26156 +DOI: 10.17226/26156 Citation: Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318–340. doi: 10.1016/j.watres.2013.10.045. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2013.10.045 +DOI: 10.1016/j.watres.2013.10.045 Citation: De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631–657. doi: 10.1002/etc.4935. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/etc.4935 +DOI: 10.1002/etc.4935 Citation: Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000–2015. Environ. Res. 2017;157:87–95. doi: 10.1016/j.envres.2017.05.013. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2017.05.013 +DOI: 10.1016/j.envres.2017.05.013 Citation: Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648–108648. doi: 10.1016/j.envres.2019.108648. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envres.2019.108648 +DOI: 10.1016/j.envres.2019.108648 Citation: Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101–113. doi: 10.1016/j.envpol.2019.02.018. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2019.02.018 +DOI: 10.1016/j.envpol.2019.02.018 Citation: Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622–141622. doi: 10.1016/j.scitotenv.2020.141622. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.scitotenv.2020.141622 +DOI: 10.1016/j.scitotenv.2020.141622 Citation: Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295–118295. doi: 10.1016/j.watres.2022.118295. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.watres.2022.118295 +DOI: 10.1016/j.watres.2022.118295 Citation: Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9–18. doi: 10.1016/j.chemosphere.2016.12.057. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2016.12.057 +DOI: 10.1016/j.chemosphere.2016.12.057 Citation: Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530–541. doi: 10.1039/b701417a. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1039/b701417a +DOI: 10.1039/b701417a Citation: Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887–1898. Title: None @@ -2897,25 +2897,25 @@ Citation: Pétré MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c07978 +DOI: 10.1021/acs.est.0c07978 Citation: Ahrens L, Norström K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33–38. doi: 10.1016/j.chemosphere.2014.03.136. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.chemosphere.2014.03.136 +DOI: 10.1016/j.chemosphere.2014.03.136 Citation: Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768–15777. doi: 10.1021/acs.est.0c04472. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.est.0c04472 +DOI: 10.1021/acs.est.0c04472 Citation: Quinnan J, et al. Application of PFAS‐mobile lab to support adaptive characterization and flux‐based conceptual site models at AFFF releases. Remed. J. 2021;31:7–26. doi: 10.1002/rem.21680. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/rem.21680 +DOI: 10.1002/rem.21680 Citation: Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291–301. Title: None @@ -2927,37 +2927,37 @@ Citation: Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3389/fenvs.2021.796026 +DOI: 10.3389/fenvs.2021.796026 Citation: Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344–350. doi: 10.1021/acs.estlett.6b00260. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.estlett.6b00260 +DOI: 10.1021/acs.estlett.6b00260 Citation: Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per‐and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163–174. doi: 10.1002/ieam.4614. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/ieam.4614 +DOI: 10.1002/ieam.4614 Citation: Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54–65. doi: 10.1110/ps.073138508. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1110/ps.073138508 +DOI: 10.1110/ps.073138508 Citation: Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1–9. doi: 10.1038/sdata.2016.18. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2016.18 +DOI: 10.1038/sdata.2016.18 Citation: Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931–936. doi: 10.1038/s41431-018-0160-0. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41431-018-0160-0 +DOI: 10.1038/s41431-018-0160-0 Citation: Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023). Title: None @@ -2969,17 +2969,17 @@ Citation: Zsóka Á, Szerényi ZM, Széchy A, Kocsis T. Greening due to environm Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.jclepro.2012.11.030 +DOI: 10.1016/j.jclepro.2012.11.030 Citation: Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505–513. doi: 10.1016/j.envpol.2018.01.066. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.envpol.2018.01.066 +DOI: 10.1016/j.envpol.2018.01.066 Citation: Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare. Title: None PMID: None PMCID: None -DOI: https://doi.org/10.6084/m9.figshare.15218958 +DOI: 10.6084/m9.figshare.15218958 diff --git a/tests/testing_files/intermediate_results/author_search/all/publication_dict.json b/tests/testing_files/intermediate_results/author_search/all/publication_dict.json index 790ab73..0dd85eb 100644 --- a/tests/testing_files/intermediate_results/author_search/all/publication_dict.json +++ b/tests/testing_files/intermediate_results/author_search/all/publication_dict.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -216,7 +217,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +241,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +346,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +702,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +727,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1103,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1244,163 +1245,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1408,76 +1409,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1532,7 +1533,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1554,17 +1555,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1585,69 +1586,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1668,21 +1669,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1696,14 +1697,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1715,37 +1716,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1764,16 +1765,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1811,7 +1812,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1833,6 +1834,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar", "Crossref" ], @@ -1845,24 +1847,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1882,7 +1884,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1901,10 +1903,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1917,15 +1919,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1962,7 +1964,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1999,38 +2001,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2071,15 +2073,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2090,31 +2092,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2176,7 +2178,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2196,8 +2198,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2210,14 +2212,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2236,24 +2238,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2264,31 +2266,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2313,31 +2315,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2350,36 +2352,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2392,7 +2394,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2404,24 +2406,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2434,120 +2436,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2558,24 +2560,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2586,361 +2588,88 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. 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Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/533452a", - "pubmed_id": null, - "title": null + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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"citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", - 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "ORCID": null, - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "grants": [ - "2020026", - "P42 ES007380", - "U54 TR001998-05A1" - ], - "journal": "PloS one", - "keywords": [], - "methods": null, - "publication_date": { - "day": 19, - "month": 11, - "year": 2022 - }, - "pubmed_id": "36399468", - "queried_sources": [ - "PubMed", - "ORCID", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Consolidated Appropriations Act of 2008, H.R. 2764, Editor. 2008: Congressional Record.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": "https://doi.org/10.1073/pnas.98.2.381", - "pubmed_id": null, - "title": "PubMed Central: The GenBank of the published literature" - }, - { - "PMCID": null, - "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", + "title": "PubMed Central: The GenBank of the published literature" + }, + { + "PMCID": "PMC3016663", + "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", + "doi": null, + "pubmed_id": "21243064", "title": null }, { @@ -3027,7 +2756,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -3062,555 +2791,352 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" - }, - { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3697,7 +3223,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3734,379 +3260,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4136,7 +3662,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4169,35 +3695,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4210,36 +3736,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4252,7 +3778,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4294,15 +3820,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { @@ -4338,19 +3864,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -4371,19 +3898,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/all/running_pubs1.json b/tests/testing_files/intermediate_results/author_search/all/running_pubs1.json index e62e5ff..da839d2 100644 --- a/tests/testing_files/intermediate_results/author_search/all/running_pubs1.json +++ b/tests/testing_files/intermediate_results/author_search/all/running_pubs1.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1172,163 +1172,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1336,76 +1336,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1460,7 +1460,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1478,17 +1478,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1509,63 +1509,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1592,21 +1592,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1620,7 +1620,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1639,24 +1639,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1688,16 +1688,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1735,7 +1735,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1767,24 +1767,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1823,10 +1823,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1839,15 +1839,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1884,7 +1884,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1916,38 +1916,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1993,10 +1993,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2007,31 +2007,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2093,7 +2093,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2111,8 +2111,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2125,14 +2125,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2151,24 +2151,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2179,31 +2179,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2228,31 +2228,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2270,31 +2270,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2307,7 +2307,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2319,24 +2319,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2349,120 +2349,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2473,24 +2473,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2501,10 +2501,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2542,7 +2542,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2565,17 +2565,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2662,7 +2662,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2694,150 +2694,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2850,22 +2850,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2878,7 +2878,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -2920,7 +2920,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -2948,8 +2948,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -2969,15 +2969,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3126,7 +3126,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3161,379 +3161,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3563,7 +3563,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3592,35 +3592,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3633,36 +3633,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3717,15 +3717,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/all/running_pubs2.json b/tests/testing_files/intermediate_results/author_search/all/running_pubs2.json index a9f732f..3ed5915 100644 --- a/tests/testing_files/intermediate_results/author_search/all/running_pubs2.json +++ b/tests/testing_files/intermediate_results/author_search/all/running_pubs2.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1173,163 +1173,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1337,76 +1337,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1461,7 +1461,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1480,17 +1480,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1511,63 +1511,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1594,21 +1594,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1622,7 +1622,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1641,24 +1641,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1690,16 +1690,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1737,7 +1737,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1758,7 +1758,8 @@ }, "pubmed_id": "36870946", "queried_sources": [ - "PubMed" + "PubMed", + "ORCID" ], "references": [ { @@ -1769,24 +1770,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1825,10 +1826,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1841,15 +1842,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1886,7 +1887,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1919,38 +1920,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1996,10 +1997,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2010,31 +2011,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2096,7 +2097,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2114,8 +2115,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2128,14 +2129,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2154,24 +2155,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2182,31 +2183,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2231,31 +2232,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2273,31 +2274,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2310,7 +2311,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2322,24 +2323,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2352,120 +2353,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2476,24 +2477,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2504,10 +2505,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2545,7 +2546,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2569,17 +2570,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2666,7 +2667,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2699,150 +2700,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2855,22 +2856,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2883,7 +2884,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -2925,7 +2926,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -2953,8 +2954,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -2974,15 +2975,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3131,7 +3132,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3167,379 +3168,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3569,7 +3570,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3599,35 +3600,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3640,36 +3641,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3724,15 +3725,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/all/running_pubs3.json b/tests/testing_files/intermediate_results/author_search/all/running_pubs3.json index b2c44de..5cc7201 100644 --- a/tests/testing_files/intermediate_results/author_search/all/running_pubs3.json +++ b/tests/testing_files/intermediate_results/author_search/all/running_pubs3.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1242,163 +1242,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1406,76 +1406,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1530,7 +1530,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1550,17 +1550,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1581,63 +1581,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1664,21 +1664,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1692,7 +1692,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1711,24 +1711,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1760,16 +1760,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1807,7 +1807,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1829,6 +1829,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar" ], "references": [ @@ -1840,24 +1841,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1896,10 +1897,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1912,15 +1913,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1957,7 +1958,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1991,38 +1992,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,10 +2069,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2082,31 +2083,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2168,7 +2169,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2187,8 +2188,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2201,14 +2202,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2227,24 +2228,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2255,31 +2256,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2304,31 +2305,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2346,31 +2347,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2383,7 +2384,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2395,24 +2396,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2425,120 +2426,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2549,24 +2550,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2577,10 +2578,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2618,7 +2619,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2643,17 +2644,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2740,7 +2741,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2774,150 +2775,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2930,22 +2931,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2958,7 +2959,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -3000,7 +3001,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -3028,8 +3029,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -3049,15 +3050,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3206,7 +3207,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3243,379 +3244,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3645,7 +3646,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3676,35 +3677,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3717,36 +3718,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3801,15 +3802,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/all/running_pubs4.json b/tests/testing_files/intermediate_results/author_search/all/running_pubs4.json index 790ab73..700ac0e 100644 --- a/tests/testing_files/intermediate_results/author_search/all/running_pubs4.json +++ b/tests/testing_files/intermediate_results/author_search/all/running_pubs4.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1244,163 +1244,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1408,76 +1408,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1532,7 +1532,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1554,17 +1554,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1585,69 +1585,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1668,21 +1668,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1696,14 +1696,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1715,37 +1715,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1764,16 +1764,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1811,7 +1811,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1833,6 +1833,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar", "Crossref" ], @@ -1845,24 +1846,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1882,7 +1883,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1901,10 +1902,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1917,15 +1918,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1962,7 +1963,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1999,38 +2000,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2071,15 +2072,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2090,31 +2091,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2176,7 +2177,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2196,8 +2197,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2210,14 +2211,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2236,24 +2237,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2264,31 +2265,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2313,31 +2314,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2350,36 +2351,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2392,7 +2393,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2404,24 +2405,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2434,120 +2435,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2558,24 +2559,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2586,1031 +2587,555 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/533452a", - "pubmed_id": null, - "title": null + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", + "doi": "10.1371/journal.pone.0277834", + "grants": [ + "2020026", + "P42 ES007380", + "U54 TR001998-05A1" + ], + "journal": "PloS one", + "keywords": [], + "methods": null, + "publication_date": { + "day": 19, + "month": 11, + "year": 2022 + }, + "pubmed_id": "36399468", + "queried_sources": [ + "PubMed", + "ORCID", + "Google Scholar", + "Crossref" + ], + "references": [ { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.17226/25116", + "citation": "Consolidated Appropriations Act of 2008, H.R. 2764, Editor. 2008: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", + "title": "PubMed Central: The GenBank of the published literature" + }, + { + "PMCID": "PMC3016663", + "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", + "doi": null, + "pubmed_id": "21243064", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "citation": "Dylla F., CHORUS\u2013A solution for public access. Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", - 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. 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Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Haak L.L., et al.., ORCID: a system to uniquely identify researchers. 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Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3697,7 +3222,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3734,379 +3259,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4136,7 +3661,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4169,35 +3694,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4210,36 +3735,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4252,7 +3777,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4294,15 +3819,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/all/running_pubs5.json b/tests/testing_files/intermediate_results/author_search/all/running_pubs5.json index 790ab73..700ac0e 100644 --- a/tests/testing_files/intermediate_results/author_search/all/running_pubs5.json +++ b/tests/testing_files/intermediate_results/author_search/all/running_pubs5.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1244,163 +1244,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1408,76 +1408,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1532,7 +1532,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1554,17 +1554,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1585,69 +1585,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1668,21 +1668,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1696,14 +1696,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1715,37 +1715,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1764,16 +1764,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1811,7 +1811,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1833,6 +1833,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar", "Crossref" ], @@ -1845,24 +1846,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1882,7 +1883,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1901,10 +1902,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1917,15 +1918,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1962,7 +1963,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1999,38 +2000,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2071,15 +2072,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2090,31 +2091,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2176,7 +2177,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2196,8 +2197,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2210,14 +2211,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2236,24 +2237,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2264,31 +2265,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2313,31 +2314,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2350,36 +2351,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2392,7 +2393,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2404,24 +2405,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2434,120 +2435,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2558,24 +2559,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2586,1031 +2587,555 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/533452a", - "pubmed_id": null, - "title": null + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "ORCID": null, - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. 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Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "citation": "Haak L.L., et al.., ORCID: a system to uniquely identify researchers. Learned publishing, 2012. 25(4): p. 259\u2013264.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "citation": "Jacs\u00f3 P., Google Scholar: the pros and the cons. Online information review, 2005.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3697,7 +3222,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3734,379 +3259,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4136,7 +3661,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4169,35 +3694,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4210,36 +3735,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4252,7 +3777,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4294,15 +3819,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/all/running_pubs6.json b/tests/testing_files/intermediate_results/author_search/all/running_pubs6.json index 790ab73..0dd85eb 100644 --- a/tests/testing_files/intermediate_results/author_search/all/running_pubs6.json +++ b/tests/testing_files/intermediate_results/author_search/all/running_pubs6.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -216,7 +217,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +241,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +346,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +702,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +727,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1103,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1244,163 +1245,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1408,76 +1409,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1532,7 +1533,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1554,17 +1555,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1585,69 +1586,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1668,21 +1669,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1696,14 +1697,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1715,37 +1716,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1764,16 +1765,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1811,7 +1812,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1833,6 +1834,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar", "Crossref" ], @@ -1845,24 +1847,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1882,7 +1884,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1901,10 +1903,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1917,15 +1919,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1962,7 +1964,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1999,38 +2001,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2071,15 +2073,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2090,31 +2092,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2176,7 +2178,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2196,8 +2198,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2210,14 +2212,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2236,24 +2238,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2264,31 +2266,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2313,31 +2315,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2350,36 +2352,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2392,7 +2394,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2404,24 +2406,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2434,120 +2436,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2558,24 +2560,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2586,361 +2588,88 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. 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"citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - 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Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" - }, - { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. 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Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. 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Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3697,7 +3223,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3734,379 +3260,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4136,7 +3662,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4169,35 +3695,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4210,36 +3736,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4252,7 +3778,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4294,15 +3820,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { @@ -4338,19 +3864,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -4371,19 +3898,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/all/running_pubs7.json b/tests/testing_files/intermediate_results/author_search/all/running_pubs7.json index 790ab73..0dd85eb 100644 --- a/tests/testing_files/intermediate_results/author_search/all/running_pubs7.json +++ b/tests/testing_files/intermediate_results/author_search/all/running_pubs7.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -216,7 +217,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +241,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +346,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +702,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +727,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1103,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1244,163 +1245,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1408,76 +1409,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1532,7 +1533,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1554,17 +1555,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1585,69 +1586,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1668,21 +1669,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1696,14 +1697,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1715,37 +1716,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1764,16 +1765,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1811,7 +1812,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1833,6 +1834,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar", "Crossref" ], @@ -1845,24 +1847,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1882,7 +1884,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1901,10 +1903,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1917,15 +1919,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1962,7 +1964,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1999,38 +2001,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2071,15 +2073,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2090,31 +2092,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2176,7 +2178,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2196,8 +2198,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2210,14 +2212,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2236,24 +2238,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2264,31 +2266,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2313,31 +2315,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2350,36 +2352,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2392,7 +2394,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2404,24 +2406,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2434,120 +2436,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2558,24 +2560,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2586,361 +2588,88 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. 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Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. 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Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4136,7 +3662,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4169,35 +3695,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4210,36 +3736,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4252,7 +3778,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4294,15 +3820,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { @@ -4338,19 +3864,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -4371,19 +3898,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/all/running_pubs8.json b/tests/testing_files/intermediate_results/author_search/all/running_pubs8.json index 790ab73..0dd85eb 100644 --- a/tests/testing_files/intermediate_results/author_search/all/running_pubs8.json +++ b/tests/testing_files/intermediate_results/author_search/all/running_pubs8.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -216,7 +217,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +241,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +346,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +702,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +727,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1103,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1244,163 +1245,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1408,76 +1409,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1532,7 +1533,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1554,17 +1555,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1585,69 +1586,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1668,21 +1669,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1696,14 +1697,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1715,37 +1716,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1764,16 +1765,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1811,7 +1812,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1833,6 +1834,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar", "Crossref" ], @@ -1845,24 +1847,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1882,7 +1884,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1901,10 +1903,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1917,15 +1919,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1962,7 +1964,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1999,38 +2001,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2071,15 +2073,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2090,31 +2092,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2176,7 +2178,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2196,8 +2198,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2210,14 +2212,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2236,24 +2238,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2264,31 +2266,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2313,31 +2315,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2350,36 +2352,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2392,7 +2394,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2404,24 +2406,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2434,120 +2436,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2558,24 +2560,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2586,361 +2588,88 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/533452a", - "pubmed_id": null, - "title": null + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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"citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - 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"PMCID": "PMC9674155", - "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "ORCID": null, - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": "https://doi.org/10.1073/pnas.98.2.381", - "pubmed_id": null, - "title": "PubMed Central: The GenBank of the published literature" - }, - { - "PMCID": null, - "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", + "title": "PubMed Central: The GenBank of the published literature" + }, + { + "PMCID": "PMC3016663", + "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", + "doi": null, + "pubmed_id": "21243064", "title": null }, { @@ -3027,7 +2756,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -3062,555 +2791,352 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. 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Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. 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Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. 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Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4136,7 +3662,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4169,35 +3695,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4210,36 +3736,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4252,7 +3778,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4294,15 +3820,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { @@ -4338,19 +3864,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -4371,19 +3898,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/no_Crossref/publication_dict.json b/tests/testing_files/intermediate_results/author_search/no_Crossref/publication_dict.json index b2c44de..e210f53 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Crossref/publication_dict.json +++ b/tests/testing_files/intermediate_results/author_search/no_Crossref/publication_dict.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -216,7 +217,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +241,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +346,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +702,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +727,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1103,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1242,163 +1243,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1406,76 +1407,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1530,7 +1531,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1550,17 +1551,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1581,63 +1582,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1664,21 +1665,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1692,7 +1693,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1711,24 +1712,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1760,16 +1761,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1807,7 +1808,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1829,6 +1830,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar" ], "references": [ @@ -1840,24 +1842,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1896,10 +1898,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1912,15 +1914,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1957,7 +1959,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1991,38 +1993,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,10 +2070,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2082,31 +2084,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2168,7 +2170,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2187,8 +2189,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2201,14 +2203,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2227,24 +2229,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2255,31 +2257,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2304,31 +2306,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2346,31 +2348,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2383,7 +2385,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2395,24 +2397,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2425,120 +2427,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2549,24 +2551,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2577,10 +2579,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2618,7 +2620,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2643,17 +2645,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC33354", "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2740,7 +2742,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2774,150 +2776,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2930,22 +2932,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2958,7 +2960,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -3000,7 +3002,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -3028,8 +3030,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -3049,15 +3051,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3206,7 +3208,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3243,379 +3245,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3645,7 +3647,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3676,35 +3678,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3717,36 +3719,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3801,15 +3803,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { @@ -3845,19 +3847,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -3878,19 +3881,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs1.json b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs1.json index e62e5ff..da839d2 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs1.json +++ b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs1.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1172,163 +1172,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1336,76 +1336,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1460,7 +1460,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1478,17 +1478,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1509,63 +1509,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1592,21 +1592,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1620,7 +1620,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1639,24 +1639,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1688,16 +1688,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1735,7 +1735,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1767,24 +1767,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1823,10 +1823,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1839,15 +1839,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1884,7 +1884,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1916,38 +1916,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1993,10 +1993,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2007,31 +2007,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2093,7 +2093,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2111,8 +2111,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2125,14 +2125,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2151,24 +2151,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2179,31 +2179,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2228,31 +2228,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2270,31 +2270,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2307,7 +2307,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2319,24 +2319,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2349,120 +2349,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2473,24 +2473,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2501,10 +2501,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2542,7 +2542,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2565,17 +2565,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2662,7 +2662,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2694,150 +2694,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2850,22 +2850,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2878,7 +2878,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -2920,7 +2920,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -2948,8 +2948,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -2969,15 +2969,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3126,7 +3126,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3161,379 +3161,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3563,7 +3563,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3592,35 +3592,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3633,36 +3633,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3717,15 +3717,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs2.json b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs2.json index a9f732f..3ed5915 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs2.json +++ b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs2.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1173,163 +1173,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1337,76 +1337,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1461,7 +1461,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1480,17 +1480,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1511,63 +1511,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1594,21 +1594,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1622,7 +1622,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1641,24 +1641,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1690,16 +1690,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1737,7 +1737,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1758,7 +1758,8 @@ }, "pubmed_id": "36870946", "queried_sources": [ - "PubMed" + "PubMed", + "ORCID" ], "references": [ { @@ -1769,24 +1770,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1825,10 +1826,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1841,15 +1842,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1886,7 +1887,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1919,38 +1920,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1996,10 +1997,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2010,31 +2011,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2096,7 +2097,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2114,8 +2115,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2128,14 +2129,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2154,24 +2155,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2182,31 +2183,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2231,31 +2232,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2273,31 +2274,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2310,7 +2311,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2322,24 +2323,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2352,120 +2353,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2476,24 +2477,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2504,10 +2505,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2545,7 +2546,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2569,17 +2570,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2666,7 +2667,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2699,150 +2700,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2855,22 +2856,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2883,7 +2884,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -2925,7 +2926,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -2953,8 +2954,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -2974,15 +2975,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3131,7 +3132,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3167,379 +3168,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3569,7 +3570,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3599,35 +3600,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3640,36 +3641,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3724,15 +3725,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs3.json b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs3.json index b2c44de..5cc7201 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs3.json +++ b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs3.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1242,163 +1242,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1406,76 +1406,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1530,7 +1530,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. 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Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1664,21 +1664,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1692,7 +1692,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1711,24 +1711,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1760,16 +1760,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1807,7 +1807,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1829,6 +1829,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar" ], "references": [ @@ -1840,24 +1841,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1896,10 +1897,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1912,15 +1913,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1957,7 +1958,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1991,38 +1992,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,10 +2069,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2082,31 +2083,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2168,7 +2169,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2187,8 +2188,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2201,14 +2202,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2227,24 +2228,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2255,31 +2256,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2304,31 +2305,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2346,31 +2347,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2383,7 +2384,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2395,24 +2396,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2425,120 +2426,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2549,24 +2550,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2577,10 +2578,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2618,7 +2619,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2643,17 +2644,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2740,7 +2741,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2774,150 +2775,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2930,22 +2931,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2958,7 +2959,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -3000,7 +3001,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -3028,8 +3029,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -3049,15 +3050,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3206,7 +3207,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3243,379 +3244,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3645,7 +3646,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3676,35 +3677,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3717,36 +3718,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3801,15 +3802,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs4.json b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs4.json index b2c44de..5cc7201 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs4.json +++ b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs4.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1242,163 +1242,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1406,76 +1406,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1530,7 +1530,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1550,17 +1550,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1581,63 +1581,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1664,21 +1664,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1692,7 +1692,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1711,24 +1711,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1760,16 +1760,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1807,7 +1807,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1829,6 +1829,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar" ], "references": [ @@ -1840,24 +1841,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1896,10 +1897,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1912,15 +1913,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1957,7 +1958,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1991,38 +1992,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,10 +2069,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2082,31 +2083,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2168,7 +2169,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2187,8 +2188,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2201,14 +2202,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2227,24 +2228,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2255,31 +2256,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2304,31 +2305,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2346,31 +2347,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2383,7 +2384,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2395,24 +2396,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2425,120 +2426,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2549,24 +2550,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2577,10 +2578,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2618,7 +2619,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2643,17 +2644,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2740,7 +2741,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2774,150 +2775,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2930,22 +2931,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2958,7 +2959,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -3000,7 +3001,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -3028,8 +3029,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -3049,15 +3050,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3206,7 +3207,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3243,379 +3244,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3645,7 +3646,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3676,35 +3677,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3717,36 +3718,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3801,15 +3802,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs5.json b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs5.json index b2c44de..e210f53 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs5.json +++ b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs5.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -216,7 +217,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +241,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +346,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +702,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +727,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1103,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1242,163 +1243,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1406,76 +1407,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1530,7 +1531,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. 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Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1664,21 +1665,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1692,7 +1693,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1711,24 +1712,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1760,16 +1761,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1807,7 +1808,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1829,6 +1830,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar" ], "references": [ @@ -1840,24 +1842,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1896,10 +1898,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1912,15 +1914,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1957,7 +1959,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1991,38 +1993,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,10 +2070,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2082,31 +2084,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2168,7 +2170,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2187,8 +2189,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2201,14 +2203,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2227,24 +2229,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2255,31 +2257,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2304,31 +2306,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2346,31 +2348,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2383,7 +2385,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2395,24 +2397,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2425,120 +2427,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2549,24 +2551,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2577,10 +2579,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2618,7 +2620,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2643,17 +2645,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC33354", "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2740,7 +2742,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2774,150 +2776,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2930,22 +2932,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2958,7 +2960,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -3000,7 +3002,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -3028,8 +3030,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -3049,15 +3051,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3206,7 +3208,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3243,379 +3245,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3645,7 +3647,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3676,35 +3678,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3717,36 +3719,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3801,15 +3803,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { @@ -3845,19 +3847,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -3878,19 +3881,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs6.json b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs6.json index b2c44de..e210f53 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs6.json +++ b/tests/testing_files/intermediate_results/author_search/no_Crossref/running_pubs6.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -216,7 +217,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +241,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +346,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +702,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +727,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1103,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1242,163 +1243,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1406,76 +1407,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1530,7 +1531,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1550,17 +1551,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1581,63 +1582,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1664,21 +1665,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1692,7 +1693,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1711,24 +1712,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1760,16 +1761,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1807,7 +1808,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1829,6 +1830,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Google Scholar" ], "references": [ @@ -1840,24 +1842,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1896,10 +1898,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1912,15 +1914,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1957,7 +1959,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1991,38 +1993,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,10 +2070,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2082,31 +2084,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2168,7 +2170,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2187,8 +2189,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2201,14 +2203,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2227,24 +2229,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2255,31 +2257,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2304,31 +2306,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2346,31 +2348,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2383,7 +2385,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2395,24 +2397,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2425,120 +2427,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2549,24 +2551,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2577,10 +2579,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2618,7 +2620,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2643,17 +2645,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC33354", "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2740,7 +2742,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2774,150 +2776,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2930,22 +2932,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2958,7 +2960,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -3000,7 +3002,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -3028,8 +3030,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -3049,15 +3051,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3206,7 +3208,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3243,379 +3245,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3645,7 +3647,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3676,35 +3678,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3717,36 +3719,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3801,15 +3803,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { @@ -3845,19 +3847,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -3878,19 +3881,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/publication_dict.json b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/publication_dict.json index 46e0c44..5c6a9b1 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/publication_dict.json +++ b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/publication_dict.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1175,163 +1175,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1339,76 +1339,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1463,7 +1463,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1484,17 +1484,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1515,69 +1515,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1598,21 +1598,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1626,14 +1626,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1645,37 +1645,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1694,16 +1694,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1741,7 +1741,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1763,6 +1763,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Crossref" ], "references": [ @@ -1774,24 +1775,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1811,7 +1812,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1830,10 +1831,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1846,15 +1847,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1891,7 +1892,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1927,38 +1928,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1999,15 +2000,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2018,31 +2019,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2104,7 +2105,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2123,8 +2124,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2137,14 +2138,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2163,24 +2164,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2191,31 +2192,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2240,31 +2241,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2277,36 +2278,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2319,7 +2320,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2331,24 +2332,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2361,120 +2362,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2485,24 +2486,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2513,1029 +2514,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" + }, + { + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", + "title": "PubMed Central: The GenBank of the published literature" + }, + { + "PMCID": "PMC3016663", + "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", + "doi": null, + "pubmed_id": "21243064", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "citation": "Dylla F., CHORUS\u2013A solution for public access. Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", - 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "ORCID": null, - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "grants": [ - "2020026", - "P42 ES007380", - "U54 TR001998-05A1" - ], - "journal": "PloS one", - "keywords": [], - "methods": null, - "publication_date": { - "day": 19, - "month": 11, - "year": 2022 - }, - "pubmed_id": "36399468", - "queried_sources": [ - "PubMed", - "ORCID", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Consolidated Appropriations Act of 2008, H.R. 2764, Editor. 2008: Congressional Record.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": "https://doi.org/10.1073/pnas.98.2.381", - "pubmed_id": null, - "title": "PubMed Central: The GenBank of the published literature" - }, - { - "PMCID": null, - "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dylla F., CHORUS\u2013A solution for public access. Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Haak L.L., et al.., ORCID: a system to uniquely identify researchers. 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Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. 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Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. 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Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3622,7 +3147,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3658,379 +3183,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4060,7 +3585,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4092,35 +3617,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4133,36 +3658,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4175,7 +3700,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4217,15 +3742,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs1.json b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs1.json index e62e5ff..da839d2 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs1.json +++ b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs1.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1172,163 +1172,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1336,76 +1336,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1460,7 +1460,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1478,17 +1478,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1509,63 +1509,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1592,21 +1592,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1620,7 +1620,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1639,24 +1639,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1688,16 +1688,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1735,7 +1735,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1767,24 +1767,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1823,10 +1823,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1839,15 +1839,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1884,7 +1884,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1916,38 +1916,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1993,10 +1993,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2007,31 +2007,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2093,7 +2093,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2111,8 +2111,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2125,14 +2125,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2151,24 +2151,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2179,31 +2179,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2228,31 +2228,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2270,31 +2270,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2307,7 +2307,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2319,24 +2319,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2349,120 +2349,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2473,24 +2473,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2501,10 +2501,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2542,7 +2542,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2565,17 +2565,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2662,7 +2662,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2694,150 +2694,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2850,22 +2850,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2878,7 +2878,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -2920,7 +2920,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -2948,8 +2948,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -2969,15 +2969,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3126,7 +3126,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3161,379 +3161,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3563,7 +3563,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3592,35 +3592,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3633,36 +3633,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3717,15 +3717,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs2.json b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs2.json index a9f732f..3ed5915 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs2.json +++ b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs2.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1173,163 +1173,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1337,76 +1337,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1461,7 +1461,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1480,17 +1480,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1511,63 +1511,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1594,21 +1594,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1622,7 +1622,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1641,24 +1641,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1690,16 +1690,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1737,7 +1737,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1758,7 +1758,8 @@ }, "pubmed_id": "36870946", "queried_sources": [ - "PubMed" + "PubMed", + "ORCID" ], "references": [ { @@ -1769,24 +1770,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1825,10 +1826,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1841,15 +1842,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1886,7 +1887,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1919,38 +1920,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1996,10 +1997,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2010,31 +2011,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2096,7 +2097,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2114,8 +2115,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2128,14 +2129,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2154,24 +2155,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2182,31 +2183,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2231,31 +2232,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2273,31 +2274,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2310,7 +2311,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2322,24 +2323,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2352,120 +2353,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2476,24 +2477,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2504,10 +2505,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2545,7 +2546,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2569,17 +2570,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2666,7 +2667,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2699,150 +2700,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2855,22 +2856,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2883,7 +2884,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -2925,7 +2926,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -2953,8 +2954,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -2974,15 +2975,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3131,7 +3132,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3167,379 +3168,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3569,7 +3570,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3599,35 +3600,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3640,36 +3641,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3724,15 +3725,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs3.json b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs3.json index 46e0c44..5c6a9b1 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs3.json +++ b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs3.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1175,163 +1175,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1339,76 +1339,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1463,7 +1463,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1484,17 +1484,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1515,69 +1515,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1598,21 +1598,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1626,14 +1626,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1645,37 +1645,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1694,16 +1694,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1741,7 +1741,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1763,6 +1763,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Crossref" ], "references": [ @@ -1774,24 +1775,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1811,7 +1812,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1830,10 +1831,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1846,15 +1847,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1891,7 +1892,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1927,38 +1928,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1999,15 +2000,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2018,31 +2019,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2104,7 +2105,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2123,8 +2124,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2137,14 +2138,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2163,24 +2164,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2191,31 +2192,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2240,31 +2241,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2277,36 +2278,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2319,7 +2320,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2331,24 +2332,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2361,120 +2362,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2485,24 +2486,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2513,1029 +2514,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" + }, + { + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "ORCID": null, - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3622,7 +3147,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3658,379 +3183,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4060,7 +3585,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4092,35 +3617,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4133,36 +3658,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4175,7 +3700,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4217,15 +3742,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs4.json b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs4.json index 46e0c44..5c6a9b1 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs4.json +++ b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs4.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1175,163 +1175,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1339,76 +1339,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1463,7 +1463,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1484,17 +1484,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1515,69 +1515,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1598,21 +1598,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1626,14 +1626,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1645,37 +1645,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1694,16 +1694,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1741,7 +1741,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1763,6 +1763,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Crossref" ], "references": [ @@ -1774,24 +1775,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1811,7 +1812,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1830,10 +1831,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1846,15 +1847,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1891,7 +1892,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1927,38 +1928,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1999,15 +2000,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2018,31 +2019,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2104,7 +2105,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2123,8 +2124,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2137,14 +2138,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2163,24 +2164,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2191,31 +2192,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2240,31 +2241,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2277,36 +2278,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2319,7 +2320,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2331,24 +2332,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2361,120 +2362,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2485,24 +2486,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2513,1029 +2514,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. 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MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. 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Learned publishing, 2012. 25(4): p. 259\u2013264.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "citation": "Jacs\u00f3 P., Google Scholar: the pros and the cons. Online information review, 2005.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "citation": "Lammey R., CrossRef text and data mining services. Insights, 2015. 28(2).", "doi": null, "pubmed_id": null, - "title": null - }, + "title": "CrossRef text and data mining services" + } + ], + "results": null, + "title": "Academic Tracker: Software for tracking and reporting publications associated with authors and grants." + }, + "https://doi.org/10.3390/metabo12060515": { + "PMCID": "PMC9228344", + "abstract": "We present a novel, scan-centric method for characterizing peaks from direct injection multi-scan Fourier transform mass spectra of complex samples that utilizes frequency values derived directly from the spacing of raw ", + "authors": [ { - "PMCID": null, - "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, - "title": null + "ORCID": "0000-0001-8141-7788", + "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.\nDepartment of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA.\nResource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA.", + "author_id": null, + "firstname": "Robert M", + "initials": "RM", + "lastname": "Flight" }, { - "PMCID": null, - "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3622,7 +3147,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3658,379 +3183,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4060,7 +3585,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4092,35 +3617,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4133,36 +3658,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4175,7 +3700,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4217,15 +3742,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs5.json b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs5.json index 46e0c44..5c6a9b1 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs5.json +++ b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs5.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1175,163 +1175,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1339,76 +1339,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1463,7 +1463,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1484,17 +1484,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1515,69 +1515,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1598,21 +1598,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1626,14 +1626,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1645,37 +1645,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1694,16 +1694,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1741,7 +1741,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1763,6 +1763,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Crossref" ], "references": [ @@ -1774,24 +1775,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1811,7 +1812,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1830,10 +1831,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1846,15 +1847,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1891,7 +1892,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1927,38 +1928,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1999,15 +2000,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2018,31 +2019,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2104,7 +2105,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2123,8 +2124,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2137,14 +2138,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2163,24 +2164,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2191,31 +2192,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2240,31 +2241,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2277,36 +2278,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2319,7 +2320,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2331,24 +2332,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2361,120 +2362,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2485,24 +2486,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2513,1029 +2514,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" + }, + { + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", + "doi": "10.1371/journal.pone.0277834", + "grants": [ + "2020026", + "P42 ES007380", + "U54 TR001998-05A1" + ], + "journal": "PloS one", + "keywords": [], + "methods": null, + "publication_date": { + "day": 19, + "month": 11, + "year": 2022 + }, + "pubmed_id": "36399468", + "queried_sources": [ + "PubMed", + "ORCID", + "Crossref" + ], + "references": [ { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "citation": "Consolidated Appropriations Act of 2008, H.R. 2764, Editor. 2008: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.17226/25116", - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", + "title": "PubMed Central: The GenBank of the published literature" + }, + { + "PMCID": "PMC3016663", + "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", + "doi": null, + "pubmed_id": "21243064", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "citation": "Dylla F., CHORUS\u2013A solution for public access. Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", - 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "ORCID": null, - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3622,7 +3147,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3658,379 +3183,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4060,7 +3585,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4092,35 +3617,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4133,36 +3658,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4175,7 +3700,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4217,15 +3742,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs6.json b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs6.json index 46e0c44..5c6a9b1 100644 --- a/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs6.json +++ b/tests/testing_files/intermediate_results/author_search/no_Google_Scholar/running_pubs6.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1175,163 +1175,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1339,76 +1339,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1463,7 +1463,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1484,17 +1484,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1515,69 +1515,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1598,21 +1598,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1626,14 +1626,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1645,37 +1645,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1694,16 +1694,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1741,7 +1741,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1763,6 +1763,7 @@ "pubmed_id": "36870946", "queried_sources": [ "PubMed", + "ORCID", "Crossref" ], "references": [ @@ -1774,24 +1775,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1811,7 +1812,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1830,10 +1831,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1846,15 +1847,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1891,7 +1892,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1927,38 +1928,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1999,15 +2000,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2018,31 +2019,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2104,7 +2105,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2123,8 +2124,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2137,14 +2138,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2163,24 +2164,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2191,31 +2192,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2240,31 +2241,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2277,36 +2278,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2319,7 +2320,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2331,24 +2332,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2361,120 +2362,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2485,24 +2486,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2513,1029 +2514,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" + }, + { + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "ORCID": null, - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3622,7 +3147,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3658,379 +3183,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4060,7 +3585,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4092,35 +3617,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4133,36 +3658,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4175,7 +3700,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4217,15 +3742,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_ORCID/publication_dict.json b/tests/testing_files/intermediate_results/author_search/no_ORCID/publication_dict.json index b1dd493..51c4dcf 100644 --- a/tests/testing_files/intermediate_results/author_search/no_ORCID/publication_dict.json +++ b/tests/testing_files/intermediate_results/author_search/no_ORCID/publication_dict.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1243,163 +1243,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1407,76 +1407,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1531,7 +1531,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1552,17 +1552,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1583,69 +1583,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1666,21 +1666,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1694,14 +1694,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1713,37 +1713,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1762,16 +1762,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1809,7 +1809,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1843,24 +1843,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1880,7 +1880,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1899,10 +1899,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1915,15 +1915,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1960,7 +1960,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1996,38 +1996,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,15 +2068,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2087,31 +2087,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2173,7 +2173,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2193,8 +2193,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2207,14 +2207,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2233,24 +2233,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2261,31 +2261,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2310,31 +2310,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2347,36 +2347,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2389,7 +2389,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2401,24 +2401,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2431,120 +2431,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2555,24 +2555,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2583,1029 +2583,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. 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MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. 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Learned publishing, 2012. 25(4): p. 259\u2013264.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "citation": "Jacs\u00f3 P., Google Scholar: the pros and the cons. Online information review, 2005.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "citation": "Lammey R., CrossRef text and data mining services. Insights, 2015. 28(2).", "doi": null, "pubmed_id": null, - "title": null - }, + "title": "CrossRef text and data mining services" + } + ], + "results": null, + "title": "Academic Tracker: Software for tracking and reporting publications associated with authors and grants." + }, + "https://doi.org/10.3390/metabo12060515": { + "PMCID": "PMC9228344", + "abstract": "We present a novel, scan-centric method for characterizing peaks from direct injection multi-scan Fourier transform mass spectra of complex samples that utilizes frequency values derived directly from the spacing of raw ", + "authors": [ { - "PMCID": null, - "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, - "title": null + "ORCID": "0000-0001-8141-7788", + "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.\nDepartment of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA.\nResource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA.", + "author_id": null, + "firstname": "Robert M", + "initials": "RM", + "lastname": "Flight" }, { - "PMCID": null, - "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3692,7 +3216,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3728,379 +3252,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4130,7 +3654,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4162,35 +3686,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4203,36 +3727,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4245,7 +3769,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4287,15 +3811,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs1.json b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs1.json index e62e5ff..da839d2 100644 --- a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs1.json +++ b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs1.json @@ -150,7 +150,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -173,101 +173,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -278,213 +278,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -634,7 +634,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -658,372 +658,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1034,66 +1034,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1147,7 +1147,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1172,163 +1172,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1336,76 +1336,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1460,7 +1460,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1478,17 +1478,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1509,63 +1509,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1592,21 +1592,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1620,7 +1620,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1639,24 +1639,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1688,16 +1688,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1735,7 +1735,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1767,24 +1767,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1823,10 +1823,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1839,15 +1839,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1884,7 +1884,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1916,38 +1916,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1993,10 +1993,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2007,31 +2007,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2093,7 +2093,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2111,8 +2111,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2125,14 +2125,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2151,24 +2151,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2179,31 +2179,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2228,31 +2228,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2270,31 +2270,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2307,7 +2307,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2319,24 +2319,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2349,120 +2349,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2473,24 +2473,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2501,10 +2501,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2542,7 +2542,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2565,17 +2565,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2662,7 +2662,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2694,150 +2694,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2850,22 +2850,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2878,7 +2878,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -2920,7 +2920,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -2948,8 +2948,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -2969,15 +2969,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3126,7 +3126,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3161,379 +3161,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3563,7 +3563,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3592,35 +3592,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3633,36 +3633,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3717,15 +3717,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs2.json b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs2.json index 435cb97..3845fe6 100644 --- a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs2.json +++ b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs2.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380" ], @@ -1241,163 +1241,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": null, + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1405,76 +1405,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": null, + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1529,7 +1529,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380" ], @@ -1548,17 +1548,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "29777206", "title": null }, { @@ -1579,63 +1579,63 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -1662,21 +1662,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": null, + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": null, + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1690,7 +1690,7 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": null, + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, @@ -1709,24 +1709,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { @@ -1758,16 +1758,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1805,7 +1805,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1838,24 +1838,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10928937", "title": null }, { @@ -1894,10 +1894,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1910,15 +1910,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19304878", "title": null }, { @@ -1955,7 +1955,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380" ], @@ -1988,38 +1988,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2065,10 +2065,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2079,31 +2079,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": null, - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2165,7 +2165,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2184,8 +2184,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2198,14 +2198,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2224,24 +2224,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2252,31 +2252,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2301,31 +2301,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2343,31 +2343,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2380,7 +2380,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2392,24 +2392,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2422,120 +2422,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2546,24 +2546,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2574,10 +2574,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null } ], @@ -2615,7 +2615,7 @@ ], "conclusions": null, "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "grants": [], "journal": "PloS one", "keywords": [], @@ -2639,17 +2639,17 @@ "title": null }, { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", "title": null }, { - "PMCID": null, + "PMCID": "PMC3016663", "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21243064", "title": null }, { @@ -2736,7 +2736,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", + "doi": "10.3390/metabo12060515", "grants": [ "2020026", "1P01CA163223-01A1", @@ -2769,150 +2769,150 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4337027", "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, + "PMCID": "PMC3882318", "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, + "PMCID": "PMC1464138", "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, + "PMCID": "PMC1904337", "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, + "PMCID": "PMC5638134", "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, + "PMCID": "PMC3472505", "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC4319441", "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC6816163", "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143054", "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, + "PMCID": "PMC6153687", "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", "title": null }, { - "PMCID": null, + "PMCID": "PMC7143220", "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, + "PMCID": "PMC8622625", "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { @@ -2925,22 +2925,22 @@ { "PMCID": null, "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", "title": null }, { - "PMCID": null, + "PMCID": "PMC3738458", "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { @@ -2953,7 +2953,7 @@ { "PMCID": null, "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, @@ -2995,7 +2995,7 @@ { "PMCID": null, "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, @@ -3023,8 +3023,8 @@ { "PMCID": null, "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { @@ -3044,15 +3044,15 @@ { "PMCID": null, "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { @@ -3201,7 +3201,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3237,379 +3237,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -3639,7 +3639,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380" @@ -3669,35 +3669,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": null, + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -3710,36 +3710,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": null, + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": null }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": null }, { @@ -3794,15 +3794,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": null, + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs3.json b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs3.json index b1dd493..51c4dcf 100644 --- a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs3.json +++ b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs3.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1243,163 +1243,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1407,76 +1407,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1531,7 +1531,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1552,17 +1552,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1583,69 +1583,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1666,21 +1666,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1694,14 +1694,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1713,37 +1713,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1762,16 +1762,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1809,7 +1809,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1843,24 +1843,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1880,7 +1880,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1899,10 +1899,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1915,15 +1915,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1960,7 +1960,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1996,38 +1996,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,15 +2068,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2087,31 +2087,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2173,7 +2173,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2193,8 +2193,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2207,14 +2207,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2233,24 +2233,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2261,31 +2261,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2310,31 +2310,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2347,36 +2347,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2389,7 +2389,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2401,24 +2401,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2431,120 +2431,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2555,24 +2555,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2583,1029 +2583,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/533452a", - "pubmed_id": null, - "title": null + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", + "doi": "10.1371/journal.pone.0277834", + "grants": [ + "2020026", + "P42 ES007380", + "U54 TR001998-05A1" + ], + "journal": "PloS one", + "keywords": [], + "methods": null, + "publication_date": { + "day": 19, + "month": 11, + "year": 2022 + }, + "pubmed_id": "36399468", + "queried_sources": [ + "PubMed", + "Google Scholar", + "Crossref" + ], + "references": [ { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.17226/25116", + "citation": "Consolidated Appropriations Act of 2008, H.R. 2764, Editor. 2008: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", + "title": "PubMed Central: The GenBank of the published literature" + }, + { + "PMCID": "PMC3016663", + "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", + "doi": null, + "pubmed_id": "21243064", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "citation": "Dylla F., CHORUS\u2013A solution for public access. Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", - "pubmed_id": null, - "title": null - 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "ORCID": null, - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "author_id": null, - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "ORCID": "0000-0003-3995-5368", - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. 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Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. 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Learned publishing, 2012. 25(4): p. 259\u2013264.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "citation": "Jacs\u00f3 P., Google Scholar: the pros and the cons. Online information review, 2005.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "citation": "Lammey R., CrossRef text and data mining services. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3692,7 +3216,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3728,379 +3252,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4130,7 +3654,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4162,35 +3686,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4203,36 +3727,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4245,7 +3769,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4287,15 +3811,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs4.json b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs4.json index b1dd493..51c4dcf 100644 --- a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs4.json +++ b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs4.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1243,163 +1243,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1407,76 +1407,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1531,7 +1531,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1552,17 +1552,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1583,69 +1583,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1666,21 +1666,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1694,14 +1694,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1713,37 +1713,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1762,16 +1762,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1809,7 +1809,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1843,24 +1843,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1880,7 +1880,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1899,10 +1899,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1915,15 +1915,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1960,7 +1960,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1996,38 +1996,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,15 +2068,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2087,31 +2087,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2173,7 +2173,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2193,8 +2193,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2207,14 +2207,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2233,24 +2233,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2261,31 +2261,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2310,31 +2310,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2347,36 +2347,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2389,7 +2389,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2401,24 +2401,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2431,120 +2431,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2555,24 +2555,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2583,1029 +2583,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. 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Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. 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Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. 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Insights, 2015. 28(2).", "doi": null, "pubmed_id": null, - "title": null - }, + "title": "CrossRef text and data mining services" + } + ], + "results": null, + "title": "Academic Tracker: Software for tracking and reporting publications associated with authors and grants." + }, + "https://doi.org/10.3390/metabo12060515": { + "PMCID": "PMC9228344", + "abstract": "We present a novel, scan-centric method for characterizing peaks from direct injection multi-scan Fourier transform mass spectra of complex samples that utilizes frequency values derived directly from the spacing of raw ", + "authors": [ { - "PMCID": null, - "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3692,7 +3216,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3728,379 +3252,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4130,7 +3654,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4162,35 +3686,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4203,36 +3727,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4245,7 +3769,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4287,15 +3811,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs5.json b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs5.json index b1dd493..51c4dcf 100644 --- a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs5.json +++ b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs5.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1243,163 +1243,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1407,76 +1407,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1531,7 +1531,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1552,17 +1552,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1583,69 +1583,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1666,21 +1666,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1694,14 +1694,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1713,37 +1713,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1762,16 +1762,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1809,7 +1809,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1843,24 +1843,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1880,7 +1880,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1899,10 +1899,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1915,15 +1915,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1960,7 +1960,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1996,38 +1996,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,15 +2068,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2087,31 +2087,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2173,7 +2173,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2193,8 +2193,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2207,14 +2207,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2233,24 +2233,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2261,31 +2261,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2310,31 +2310,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2347,36 +2347,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2389,7 +2389,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2401,24 +2401,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2431,120 +2431,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2555,24 +2555,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2583,1029 +2583,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. 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L., 2015. 18: p. 267.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", - "pubmed_id": null, - "title": null - 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MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. 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Learned publishing, 2012. 25(4): p. 259\u2013264.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "citation": "Jacs\u00f3 P., Google Scholar: the pros and the cons. Online information review, 2005.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "citation": "Lammey R., CrossRef text and data mining services. Insights, 2015. 28(2).", "doi": null, "pubmed_id": null, - "title": null - }, + "title": "CrossRef text and data mining services" + } + ], + "results": null, + "title": "Academic Tracker: Software for tracking and reporting publications associated with authors and grants." + }, + "https://doi.org/10.3390/metabo12060515": { + "PMCID": "PMC9228344", + "abstract": "We present a novel, scan-centric method for characterizing peaks from direct injection multi-scan Fourier transform mass spectra of complex samples that utilizes frequency values derived directly from the spacing of raw ", + "authors": [ { - "PMCID": null, - "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, - "title": null + "ORCID": "0000-0001-8141-7788", + "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.\nDepartment of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA.\nResource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA.", + "author_id": null, + "firstname": "Robert M", + "initials": "RM", + "lastname": "Flight" }, { - "PMCID": null, - "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. 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Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4337027", + "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", + "doi": "10.1007/978-1-4939-1258-2_11", + "pubmed_id": "25270929", "title": null }, { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3882318", + "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", + "doi": "10.3390/metabo3040853", + "pubmed_id": "24404440", "title": null }, { "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3692,7 +3216,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3728,379 +3252,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4130,7 +3654,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4162,35 +3686,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4203,36 +3727,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4245,7 +3769,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4287,15 +3811,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs6.json b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs6.json index b1dd493..51c4dcf 100644 --- a/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs6.json +++ b/tests/testing_files/intermediate_results/author_search/no_ORCID/running_pubs6.json @@ -216,7 +216,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -240,101 +240,101 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC7226751", "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32260126", "title": null }, { "PMCID": null, "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29656147", "title": null }, { - "PMCID": null, + "PMCID": "PMC3079877", "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21497738", "title": null }, { - "PMCID": null, + "PMCID": "PMC2888539", "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18471545", "title": null }, { "PMCID": null, "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32044314", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28096081", "title": null }, { - "PMCID": null, + "PMCID": "PMC3830593", "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23839791", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29494209", "title": null }, { "PMCID": null, "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16118456", "title": null }, { - "PMCID": null, + "PMCID": "PMC2877836", "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20395449", "title": null }, { @@ -345,213 +345,213 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7062524", "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32997468", "title": null }, { - "PMCID": null, + "PMCID": "PMC6156397", "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30106235", "title": null }, { "PMCID": null, "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32681257", "title": null }, { "PMCID": null, "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15843085", "title": null }, { - "PMCID": null, + "PMCID": "PMC4019715", "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24361528", "title": null }, { "PMCID": null, "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30954571", "title": null }, { - "PMCID": null, + "PMCID": "PMC7700673", "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33233470", "title": null }, { "PMCID": null, "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10347117", "title": null }, { "PMCID": null, "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1576365", "title": null }, { "PMCID": null, "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6457506", "title": null }, { "PMCID": null, "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3312788", "title": null }, { "PMCID": null, "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6284782", "title": null }, { "PMCID": null, "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", "doi": null, - "pubmed_id": null, + "pubmed_id": "7007194", "title": null }, { "PMCID": null, "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", "doi": null, - "pubmed_id": null, + "pubmed_id": "6755167", "title": null }, { - "PMCID": null, + "PMCID": "PMC8570106", "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34131333", "title": null }, { - "PMCID": null, + "PMCID": "PMC8199810", "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34118892", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28468951", "title": null }, { "PMCID": null, "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20176643", "title": null }, { - "PMCID": null, + "PMCID": "PMC4067219", "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24817119", "title": null }, { - "PMCID": null, + "PMCID": "PMC8516732", "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", "doi": null, - "pubmed_id": null, + "pubmed_id": "34481731", "title": null }, { - "PMCID": null, + "PMCID": "PMC7175174", "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", "doi": null, - "pubmed_id": null, + "pubmed_id": "32131495", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC4380527", "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "25726384", "title": null }, { "PMCID": null, "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", "doi": null, - "pubmed_id": null, + "pubmed_id": "28194671", "title": null }, { "PMCID": null, "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", "doi": null, - "pubmed_id": null, + "pubmed_id": "24071517", "title": null }, { - "PMCID": null, + "PMCID": "PMC7918590", "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33673200", "title": null }, { - "PMCID": null, + "PMCID": "PMC2043489", "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17987120", "title": null }, { - "PMCID": null, + "PMCID": "PMC2988905", "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21103235", "title": null }, { - "PMCID": null, + "PMCID": "PMC6445381", "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29902522", "title": null }, { - "PMCID": null, + "PMCID": "PMC6788098", "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31632452", "title": null } ], @@ -701,7 +701,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", + "doi": "10.1038/s41467-023-35784-x", "grants": [ "133123-RSG-19-081-01-TBG", "GM121327", @@ -726,372 +726,372 @@ { "PMCID": null, "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrc2736", + "pubmed_id": "19851313", "title": null }, { - "PMCID": null, + "PMCID": "PMC4918227", "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4036", + "pubmed_id": "26845405", "title": null }, { - "PMCID": null, + "PMCID": "PMC5010480", "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/2159-8290.cd-16-0164", + "pubmed_id": "27312177", "title": null }, { - "PMCID": null, + "PMCID": "PMC208805", "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1933744100", + "pubmed_id": "14500907", "title": null }, { "PMCID": null, "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cncr.25128", + "pubmed_id": "20564407", "title": null }, { "PMCID": null, "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, + "doi": "10.3892/ijo.2013.2062", + "pubmed_id": "23969945", "title": null }, { - "PMCID": null, + "PMCID": "PMC5528390", "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molonc.2012.06.002", + "pubmed_id": "22766277", "title": null }, { - "PMCID": null, + "PMCID": "PMC4286524", "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.22188", + "pubmed_id": "25043748", "title": null }, { - "PMCID": null, + "PMCID": "PMC5385585", "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ncomms14922", + "pubmed_id": "28387316", "title": null }, { "PMCID": null, "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ccell.2015.12.006", + "pubmed_id": "26766588", "title": null }, { - "PMCID": null, + "PMCID": "PMC6279402", "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, + "doi": "10.1084/jem.20180801", + "pubmed_id": "30487290", "title": null }, { - "PMCID": null, + "PMCID": "PMC5441181", "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, + "doi": "10.7150/ijbs.19108", + "pubmed_id": "28539837", "title": null }, { "PMCID": null, "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s40265-020-01288-x", + "pubmed_id": "32166598", "title": null }, { - "PMCID": null, + "PMCID": "PMC6094952", "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.05.050", + "pubmed_id": "29898397", "title": null }, { "PMCID": null, "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", "doi": null, - "pubmed_id": null, + "pubmed_id": "35851153", "title": null }, { "PMCID": null, "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature13561", + "pubmed_id": "25119042", "title": null }, { - "PMCID": null, + "PMCID": "PMC5667640", "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4296", + "pubmed_id": "28263307", "title": null }, { "PMCID": null, "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4293", + "pubmed_id": "28263309", "title": null }, { - "PMCID": null, + "PMCID": "PMC5663148", "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s13578-017-0184-0", + "pubmed_id": "29118968", "title": null }, { "PMCID": null, "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, + "doi": "10.21873/anticanres.11198", + "pubmed_id": "27793936", "title": null }, { "PMCID": null, "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yexcr.2017.08.024", + "pubmed_id": "28823831", "title": null }, { - "PMCID": null, + "PMCID": "PMC5531293", "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2017.04.077", + "pubmed_id": "28538184", "title": null }, { "PMCID": null, "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02310", + "pubmed_id": "16613830", "title": null }, { - "PMCID": null, + "PMCID": "PMC4142810", "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2008.01.015", + "pubmed_id": "18295576", "title": null }, { "PMCID": null, "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m100636200", + "pubmed_id": "11358962", "title": null }, { - "PMCID": null, + "PMCID": "PMC5995784", "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stemcr.2018.03.013", + "pubmed_id": "29657097", "title": null }, { - "PMCID": null, + "PMCID": "PMC5451263", "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, + "doi": "10.1172/jci89950", + "pubmed_id": "28463226", "title": null }, { "PMCID": null, "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, + "doi": "10.1242/dev.02846", + "pubmed_id": "17428829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2396252", "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, + "doi": "10.1165/rcmb.2007-0350oc", + "pubmed_id": "18239190", "title": null }, { - "PMCID": null, + "PMCID": "PMC6586819", "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s42003-019-0478-3", + "pubmed_id": "31240265", "title": null }, { - "PMCID": null, + "PMCID": "PMC7319575", "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkaa407", + "pubmed_id": "32442275", "title": null }, { - "PMCID": null, + "PMCID": "PMC6612828", "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btz363", + "pubmed_id": "31510660", "title": null }, { - "PMCID": null, + "PMCID": "PMC4739640", "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nmeth.3337", + "pubmed_id": "25822800", "title": null }, { - "PMCID": null, + "PMCID": "PMC1239896", "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.0506580102", + "pubmed_id": "16199517", "title": null }, { - "PMCID": null, + "PMCID": "PMC6117512", "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, + "doi": "10.4110/in.2018.18.e27", + "pubmed_id": "30181915", "title": null }, { "PMCID": null, "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.4409", + "pubmed_id": "28985214", "title": null }, { - "PMCID": null, + "PMCID": "PMC4154057", "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nature11245", + "pubmed_id": "22955619", "title": null }, { - "PMCID": null, + "PMCID": "PMC3187920", "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cell.2011.08.017", + "pubmed_id": "21889194", "title": null }, { - "PMCID": null, + "PMCID": "PMC7961001", "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41598-021-84787-5", + "pubmed_id": "33723286", "title": null }, { - "PMCID": null, + "PMCID": "PMC6728380", "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41467-019-11867-6", + "pubmed_id": "31488816", "title": null }, { "PMCID": null, "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.prp.2022.154071", + "pubmed_id": "35985089", "title": null }, { - "PMCID": null, + "PMCID": "PMC3409442", "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.ajpath.2012.04.021", + "pubmed_id": "22713676", "title": null }, { - "PMCID": null, + "PMCID": "PMC5876441", "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", "doi": null, - "pubmed_id": null, + "pubmed_id": "29616099", "title": null }, { - "PMCID": null, + "PMCID": "PMC6342284", "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.celrep.2018.11.035", + "pubmed_id": "30517868", "title": null }, { - "PMCID": null, + "PMCID": "PMC4886303", "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nm.3968", + "pubmed_id": "26552009", "title": null }, { - "PMCID": null, + "PMCID": "PMC3625962", "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.1227604", + "pubmed_id": "23239736", "title": null }, { - "PMCID": null, + "PMCID": "PMC2580832", "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/mc.20413", + "pubmed_id": "18176935", "title": null }, { "PMCID": null, "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-04-3703", + "pubmed_id": "15604268", "title": null }, { "PMCID": null, "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, + "doi": "10.1158/0008-5472.can-05-2193", + "pubmed_id": "16288016", "title": null }, { - "PMCID": null, + "PMCID": "PMC2630502", "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.molcel.2008.10.016", + "pubmed_id": "19026780", "title": null }, { - "PMCID": null, + "PMCID": "PMC4103590", "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btu170", + "pubmed_id": "24695404", "title": null }, { - "PMCID": null, + "PMCID": "PMC3163565", "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-12-323", + "pubmed_id": "21816040", "title": null }, { - "PMCID": null, + "PMCID": "PMC2796818", "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp616", + "pubmed_id": "19910308", "title": null }, { @@ -1102,66 +1102,66 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4162509", "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "25232468", "title": null }, { "PMCID": null, "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { - "PMCID": null, + "PMCID": "PMC4010757", "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", "doi": null, - "pubmed_id": null, + "pubmed_id": "24808906", "title": null }, { - "PMCID": null, + "PMCID": "PMC4840234", "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1630", + "pubmed_id": "20436461", "title": null }, { - "PMCID": null, + "PMCID": "PMC3169432", "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/scitranslmed.3002166", + "pubmed_id": "21653829", "title": null }, { - "PMCID": null, + "PMCID": "PMC2867706", "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1000031107", + "pubmed_id": "20368440", "title": null }, { - "PMCID": null, + "PMCID": "PMC3050563", "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.stem.2010.12.007", + "pubmed_id": "21295272", "title": null }, { - "PMCID": null, + "PMCID": "PMC8743034", "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.canlet.2021.10.010", + "pubmed_id": "34655667", "title": null }, { - "PMCID": null, + "PMCID": "PMC3003123", "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, + "doi": "10.1073/pnas.1007863107", + "pubmed_id": "21098263", "title": null } ], @@ -1215,7 +1215,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -1243,163 +1243,163 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7588704", "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, + "doi": "10.1016/j.mex.2020.101111", + "pubmed_id": "33134102", "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2021.146192", + "pubmed_id": "33714836", "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, + "doi": "10.1016/j.jchromb.2021.122653", + "pubmed_id": "33839488", "title": null }, { - "PMCID": null, + "PMCID": "PMC7784712", "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33125022", "title": null }, { - "PMCID": null, + "PMCID": "PMC8015929", "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, + "doi": "10.1038/s41370-021-00316-6", + "pubmed_id": "33795841", "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2006.09.021", + "pubmed_id": "17258363", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906952", "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, + "doi": "10.1002/etc.4890", + "pubmed_id": "33017053", "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, + "doi": "10.1016/j.jenvman.2017.08.016", + "pubmed_id": "28818342", "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, + "doi": "10.17226/26156", + "pubmed_id": "35939564", "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, + "doi": "10.1016/j.watres.2013.10.045", + "pubmed_id": "24216232", "title": null }, { - "PMCID": null, + "PMCID": "PMC7906948", "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, + "doi": "10.1002/etc.4935", + "pubmed_id": "33201517", "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, + "doi": "10.1016/j.envres.2017.05.013", + "pubmed_id": "28528142", "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, + "doi": "10.1016/j.envres.2019.108648", + "pubmed_id": "31421451", "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2019.02.018", + "pubmed_id": "30784829", "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, + "doi": "10.1016/j.scitotenv.2020.141622", + "pubmed_id": "32871315", "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, + "doi": "10.1016/j.watres.2022.118295", + "pubmed_id": "35316679", "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2016.12.057", + "pubmed_id": "28002769", "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, + "doi": "10.1039/b701417a", + "pubmed_id": "17554424", "title": null }, { "PMCID": null, "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31552402", "title": null }, { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c07978", + "pubmed_id": "33797238", "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, + "doi": "10.1016/j.chemosphere.2014.03.136", + "pubmed_id": "24821232", "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, + "doi": "10.1021/acs.est.0c04472", + "pubmed_id": "33270425", "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1407,76 +1407,76 @@ "PMCID": null, "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", "doi": null, - "pubmed_id": null, + "pubmed_id": "33443261", "title": null }, { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5062567", "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, + "doi": "10.1021/acs.estlett.6b00260", + "pubmed_id": "27752509", "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC2144590", "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, + "doi": "10.1110/ps.073138508", + "pubmed_id": "18042678", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275873", "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328607", "title": null }, { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5849529", "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, + "doi": "10.1016/j.envpol.2018.01.066", + "pubmed_id": "29427949", "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1531,7 +1531,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1552,17 +1552,17 @@ ], "references": [ { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { @@ -1583,69 +1583,69 @@ "PMCID": null, "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { - "PMCID": null, + "PMCID": "PMC6324056", "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, + "doi": "10.1093/nar/gky949", + "pubmed_id": "30357364", "title": null }, { - "PMCID": null, + "PMCID": "PMC4944384", "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-3578-9_5", + "pubmed_id": "27008011", "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC7778911", "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa1062", + "pubmed_id": "33211879", "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2270403", "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, + "doi": "10.1038/nbt1206-1471", + "pubmed_id": "17160034", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1666,21 +1666,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC3817176", "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0078080", + "pubmed_id": "24223762", "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1694,14 +1694,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1713,37 +1713,37 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, + "doi": "10.1002/ieam.4614", + "pubmed_id": "35373458", "title": null }, { - "PMCID": null, + "PMCID": "PMC10275912", "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", "doi": null, - "pubmed_id": null, + "pubmed_id": "37328532", "title": null }, { - "PMCID": null, + "PMCID": "PMC9674155", "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, + "doi": "10.1371/journal.pone.0277834", + "pubmed_id": "36399468", "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1762,16 +1762,16 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC9888445", "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, + "doi": "10.6084/m9.figshare.16560144", + "pubmed_id": "35373458", "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1809,7 +1809,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1843,24 +1843,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6798127", "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, + "doi": "10.1002/pro.3715", + "pubmed_id": "31441146", "title": null }, { - "PMCID": null, + "PMCID": "PMC7779016", "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, + "doi": "10.1093/nar/gkaa970", + "pubmed_id": "33125081", "title": null }, { - "PMCID": null, + "PMCID": "PMC2447041", "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "pubmed_id": "10928937", "title": null }, { @@ -1880,7 +1880,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1899,10 +1899,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { @@ -1915,15 +1915,15 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2682512", "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btp163", + "pubmed_id": "19304878", "title": null }, { @@ -1960,7 +1960,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -1996,38 +1996,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": null }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC6018669", "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, + "doi": "10.1038/s41431-018-0160-0", + "pubmed_id": "29777206", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2068,15 +2068,15 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC5344029", "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, + "doi": "10.1016/j.cbpa.2016.12.024", + "pubmed_id": "28092796", "title": null }, { @@ -2087,31 +2087,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8444265", "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, + "doi": "10.1093/gigascience/giab060", + "pubmed_id": "34528664", "title": null }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", "doi": null, - "pubmed_id": null, + "pubmed_id": "31691833", "title": null }, { - "PMCID": null, + "PMCID": "PMC3246819", "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, + "doi": "10.1107/s0021889809008784", + "pubmed_id": "22477769", "title": null }, { - "PMCID": null, + "PMCID": "PMC1669775", "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, + "doi": "10.1093/nar/gkl971", + "pubmed_id": "17142228", "title": null } ], @@ -2173,7 +2173,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2193,8 +2193,8 @@ { "PMCID": null, "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/533452a", + "pubmed_id": "27225100", "title": null }, { @@ -2207,14 +2207,14 @@ { "PMCID": null, "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, + "doi": "10.17226/25116", + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, + "doi": "10.2777/1524", "pubmed_id": null, "title": null }, @@ -2233,24 +2233,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6594826", "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41563-019-0332-5", + "pubmed_id": "31000801", "title": null }, { "PMCID": null, "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfab157", + "pubmed_id": "34971401", "title": null }, { @@ -2261,31 +2261,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC6245499", "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pbio.2006930", + "pubmed_id": "30457984", "title": null }, { "PMCID": null, "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2771753", "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nbt.1411", + "pubmed_id": "18688244", "title": null }, { "PMCID": null, "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng1201-365", + "pubmed_id": "11726920", "title": null }, { @@ -2310,31 +2310,31 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3428019", "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ng.1054", + "pubmed_id": "22281772", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2008.0019", + "pubmed_id": "18447634", "title": null }, { "PMCID": null, "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, + "doi": "10.1089/omi.2006.10.164", + "pubmed_id": "16901222", "title": null }, { - "PMCID": null, + "PMCID": "PMC3035314", "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, + "doi": "10.4056/sigs.147362", + "pubmed_id": "21304730", "title": null }, { @@ -2347,36 +2347,36 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC9044977", "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, + "doi": "10.1289/ehp10092", + "pubmed_id": "35475652", "title": null }, { "PMCID": null, "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC7654840", "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/frai.2020.00031", + "pubmed_id": "33184612", "title": null }, { "PMCID": null, "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfm090", + "pubmed_id": "17442663", "title": null }, { @@ -2389,7 +2389,7 @@ { "PMCID": null, "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, + "doi": "10.25504/fairsharing.zrmjr7", "pubmed_id": null, "title": null }, @@ -2401,24 +2401,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC7787967", "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.comtox.2019.100096", + "pubmed_id": "33426407", "title": null }, { - "PMCID": null, + "PMCID": "PMC7153094", "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", "doi": null, - "pubmed_id": null, + "pubmed_id": "32308863", "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": null }, { @@ -2431,120 +2431,120 @@ { "PMCID": null, "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.envint.2022.107243", + "pubmed_id": "35551006", "title": null }, { - "PMCID": null, + "PMCID": "PMC2238989", "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkm755", + "pubmed_id": "17962311", "title": null }, { - "PMCID": null, + "PMCID": "PMC6944327", "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.reprotox.2019.07.012", + "pubmed_id": "31340180", "title": null }, { "PMCID": null, "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1053/j.seminoncol.2019.09.002", + "pubmed_id": "31629530", "title": null }, { - "PMCID": null, + "PMCID": "PMC5533202", "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, + "doi": "10.1182/blood-2017-03-735654", + "pubmed_id": "28600341", "title": null }, { - "PMCID": null, + "PMCID": "PMC5525192", "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/cpt.666", + "pubmed_id": "28187516", "title": null }, { "PMCID": null, "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, + "doi": "10.1515/reveh-2019-0089", + "pubmed_id": "32126018", "title": null }, { - "PMCID": null, + "PMCID": "PMC9227711", "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/acs.est.1c08383", + "pubmed_id": "35549252", "title": null }, { "PMCID": null, "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/d41586-022-02820-7", + "pubmed_id": "36064801", "title": null }, { - "PMCID": null, + "PMCID": "PMC4177145", "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/2041-1480-4-36", + "pubmed_id": "24267899", "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, + "doi": "10.1007/978-1-4939-7737-6_7", + "pubmed_id": "29761459", "title": null }, { - "PMCID": null, + "PMCID": "PMC7359286", "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/s12917-020-02451-y", + "pubmed_id": "32660541", "title": null }, { - "PMCID": null, + "PMCID": "PMC8430534", "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijerph18178985", + "pubmed_id": "34501574", "title": null }, { "PMCID": null, "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/toxsci/kfq355", + "pubmed_id": "21097997", "title": null }, { "PMCID": null, "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.toxlet.2019.04.003", + "pubmed_id": "30978436", "title": null }, { "PMCID": null, "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { - "PMCID": null, + "PMCID": "PMC2935443", "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/bioinformatics/btq415", + "pubmed_id": "20679334", "title": null }, { @@ -2555,24 +2555,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { @@ -2583,1029 +2583,553 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC8808338", "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.yrtph.2021.105020", + "pubmed_id": "34333066", "title": null + } + ], + "results": null, + "title": "A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data." + }, + "https://doi.org/10.1371/journal.pone.0277834": { + "PMCID": "PMC9674155", + "abstract": "In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", + "authors": [ + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "P Travis", + "initials": "PT", + "lastname": "Thompson" }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/533452a", - "pubmed_id": null, - "title": null + "ORCID": null, + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", + "author_id": null, + "firstname": "Christian D", + "initials": "CD", + "lastname": "Powell" }, + { + "ORCID": "0000-0003-3995-5368", + "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", + "author_id": "Hunter Moseley", + "firstname": "Hunter N B", + "initials": "HNB", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", + "doi": "10.1371/journal.pone.0277834", + "grants": [ + "2020026", + "P42 ES007380", + "U54 TR001998-05A1" + ], + "journal": "PloS one", + "keywords": [], + "methods": null, + "publication_date": { + "day": 19, + "month": 11, + "year": 2022 + }, + "pubmed_id": "36399468", + "queried_sources": [ + "PubMed", + "Google Scholar", + "Crossref" + ], + "references": [ { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.17226/25116", + "citation": "Consolidated Appropriations Act of 2008, H.R. 2764, Editor. 2008: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", - "pubmed_id": null, + "PMCID": "PMC33354", + "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", + "doi": "10.1073/pnas.98.2.381", + "pubmed_id": "11209037", + "title": "PubMed Central: The GenBank of the published literature" + }, + { + "PMCID": "PMC3016663", + "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", + "doi": null, + "pubmed_id": "21243064", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "citation": "Dylla F., CHORUS\u2013A solution for public access. Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btq415", - 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. 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Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": "https://doi.org/10.1073/pnas.98.2.381", - "pubmed_id": null, - "title": "PubMed Central: The GenBank of the published literature" - }, - { - "PMCID": null, - "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dylla F., CHORUS\u2013A solution for public access. Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Haak L.L., et al.., ORCID: a system to uniquely identify researchers. 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Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. 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Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, + "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", + "doi": "10.1038/s41374-021-00631-4", + "pubmed_id": "34193963", "title": null }, { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": "R: A Language and Environment for Statistical Computing" - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": "Python 3 Reference Manual" - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1464138", + "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", + "doi": "10.1186/1471-2105-7-234", + "pubmed_id": "16646969", "title": null }, { "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", + "doi": "10.1021/acs.analchem.9b00748", + "pubmed_id": "31260262", "title": null }, { "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": "Ggplot2: Elegant Graphics for Data Analysis" - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, + "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", + "doi": "10.1016/j.ymeth.2004.03.015", + "pubmed_id": "15283918", "title": null }, { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC1904337", + "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", + "doi": "10.1002/mas.20108", + "pubmed_id": "16921475", "title": null }, { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC5638134", + "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", + "doi": "10.1016/j.aca.2017.04.014", + "pubmed_id": "28576319", "title": null }, { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3472505", + "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", + "doi": "10.1021/ac3018795", + "pubmed_id": "22946681", "title": null }, { "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, + "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", + "doi": "10.1021/ac1011574", + "pubmed_id": "20608743", "title": null }, { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3471671", + "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", + "doi": "10.1016/j.pharmthera.2011.12.007", + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC4319441", + "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", + "doi": "10.1172/jci72873", + "pubmed_id": "25607840", "title": null }, { "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, + "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC6816163", + "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", + "doi": "10.1186/s12859-019-3096-7", + "pubmed_id": "31660850", "title": null }, { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143054", + "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", + "doi": "10.3390/metabo10030118", + "pubmed_id": "32245221", "title": null }, { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown: The Definitive Guide" - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": "R Markdown Cookbook" + "PMCID": "PMC6153687", + "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", + "doi": "10.1007/s11306-018-1426-9", + "pubmed_id": "30830442", + "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC7143220", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", + "doi": "10.3390/metabo10030122", + "pubmed_id": "32214009", "title": null }, { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", - "doi": null, - "pubmed_id": null, + "PMCID": "PMC8622625", + "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", + "doi": "10.3390/metabo11110740", + "pubmed_id": "34822397", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", + "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Local regression models" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41374-021-00631-4", - "pubmed_id": null, + "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", + "doi": "10.1021/ac00278a027", + "pubmed_id": "6524653", + "title": null + }, + { + "PMCID": "PMC3738458", + "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", + "doi": "10.1371/journal.pcbi.1003118", + "pubmed_id": "23950696", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", + "doi": "10.1101/2022.02.24.481854", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", + "doi": null, "pubmed_id": null, - "title": null + "title": "R: A Language and Environment for Statistical Computing" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Python 3 Reference Manual" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", + "doi": "10.21105/joss.02959", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", + "doi": null, "pubmed_id": null, - "title": null + "title": "Ggplot2: Elegant Graphics for Data Analysis" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", - "pubmed_id": null, + "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", + "doi": "10.1093/bioinformatics/btw313", + "pubmed_id": "27207943", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", - "pubmed_id": null, + "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", + "doi": "10.1021/acs.jproteome.0c00313", + "pubmed_id": "32902283", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", - "pubmed_id": null, + "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", + "doi": "10.1093/bioinformatics/btr645", + "pubmed_id": "22113085", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1101/2022.02.24.481854", + "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.21105/joss.02959", + "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown: The Definitive Guide" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btw313", + "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", + "doi": null, "pubmed_id": null, - "title": null + "title": "R Markdown Cookbook" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/acs.jproteome.0c00313", + "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", + "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/bioinformatics/btr645", + "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453304#.YpiiwlRBxPY.", + "doi": null, "pubmed_id": null, "title": null } @@ -3692,7 +3216,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", + "doi": "10.3390/metabo13020215", "grants": [ "P30 GM127211", "P20 GM104357", @@ -3728,379 +3252,379 @@ { "PMCID": null, "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/s2468-1253(22)00165-0", + "pubmed_id": "35798021", "title": null }, { - "PMCID": null, + "PMCID": "PMC9508552", "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, + "doi": "10.1042/cs20220572", + "pubmed_id": "36148775", "title": null }, { "PMCID": null, "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/nrgastro.2010.21", + "pubmed_id": "20195271", "title": null }, { "PMCID": null, "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41575-021-00448-y", + "pubmed_id": "33972770", "title": null }, { - "PMCID": null, + "PMCID": "PMC8238775", "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s00392-020-01709-7", + "pubmed_id": "32696080", "title": null }, { - "PMCID": null, + "PMCID": "PMC8260361", "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00405.2020", + "pubmed_id": "33284088", "title": null }, { - "PMCID": null, + "PMCID": "PMC4829185", "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0153427", + "pubmed_id": "27071062", "title": null }, { - "PMCID": null, + "PMCID": "PMC8157031", "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/molecules26102975", + "pubmed_id": "34067839", "title": null }, { - "PMCID": null, + "PMCID": "PMC6620644", "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/physiolgenomics.00028.2019", + "pubmed_id": "31074682", "title": null }, { - "PMCID": null, + "PMCID": "PMC7380202", "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.ra120.013700", + "pubmed_id": "32404366", "title": null }, { - "PMCID": null, + "PMCID": "PMC7775678", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fphar.2020.594574", + "pubmed_id": "33390979", "title": null }, { - "PMCID": null, + "PMCID": "PMC3408814", "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2012.04.005", + "pubmed_id": "22609053", "title": null }, { - "PMCID": null, + "PMCID": "PMC2858252", "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/iub.319", + "pubmed_id": "20222015", "title": null }, { - "PMCID": null, + "PMCID": "PMC2422835", "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.cellsig.2007.12.006", + "pubmed_id": "18191382", "title": null }, { - "PMCID": null, + "PMCID": "PMC7411076", "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2020.00505", + "pubmed_id": "32849291", "title": null }, { - "PMCID": null, + "PMCID": "PMC6775186", "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, + "doi": "10.3389/fendo.2019.00665", + "pubmed_id": "31616384", "title": null }, { - "PMCID": null, + "PMCID": "PMC5122784", "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.731703", + "pubmed_id": "27738106", "title": null }, { - "PMCID": null, + "PMCID": "PMC9489820", "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/hep.32467", + "pubmed_id": "35313030", "title": null }, { - "PMCID": null, + "PMCID": "PMC7554716", "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox9090889", + "pubmed_id": "32961782", "title": null }, { - "PMCID": null, + "PMCID": "PMC6879843", "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpregu.00153.2019", + "pubmed_id": "31483154", "title": null }, { - "PMCID": null, + "PMCID": "PMC5406988", "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpendo.00396.2016", + "pubmed_id": "28096081", "title": null }, { "PMCID": null, "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/anie.201602525", + "pubmed_id": "27144463", "title": null }, { "PMCID": null, "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.biomaterials.2017.06.014", + "pubmed_id": "28624706", "title": null }, { - "PMCID": null, + "PMCID": "PMC6812632", "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/atvbaha.119.313056", + "pubmed_id": "31533471", "title": null }, { - "PMCID": null, + "PMCID": "PMC6824489", "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m093096", + "pubmed_id": "31484695", "title": null }, { - "PMCID": null, + "PMCID": "PMC9126483", "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/rcm.8911", + "pubmed_id": "32738001", "title": null }, { - "PMCID": null, + "PMCID": "PMC8262718", "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkab419", + "pubmed_id": "34048582", "title": null }, { - "PMCID": null, + "PMCID": "PMC7848852", "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, + "doi": "10.12688/f1000research.28022.1", + "pubmed_id": "33564392", "title": null }, { - "PMCID": null, + "PMCID": "PMC5203696", "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m116.752311", + "pubmed_id": "27784782", "title": null }, { - "PMCID": null, + "PMCID": "PMC8750478", "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/cells11010004", + "pubmed_id": "35011564", "title": null }, { - "PMCID": null, + "PMCID": "PMC3540863", "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, + "doi": "10.1194/jlr.m020941", + "pubmed_id": "22628619", "title": null }, { - "PMCID": null, + "PMCID": "PMC2856294", "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, + "doi": "10.1074/jbc.m109.081489", + "pubmed_id": "20097939", "title": null }, { - "PMCID": null, + "PMCID": "PMC9854555", "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox12010170", + "pubmed_id": "36671031", "title": null }, { - "PMCID": null, + "PMCID": "PMC6938163", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1007/s11906-019-0994-z", + "pubmed_id": "31599366", "title": null }, { - "PMCID": null, + "PMCID": "PMC6205727", "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/hypertensionaha.118.11130", + "pubmed_id": "30354722", "title": null }, { - "PMCID": null, + "PMCID": "PMC6032063", "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajpgi.00026.2018", + "pubmed_id": "29494209", "title": null }, { - "PMCID": null, + "PMCID": "PMC5831340", "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.tem.2018.01.002", + "pubmed_id": "29409713", "title": null }, { - "PMCID": null, + "PMCID": "PMC8498001", "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.redox.2021.102152", + "pubmed_id": "34610553", "title": null }, { - "PMCID": null, + "PMCID": "PMC7764878", "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/ijms21249493", + "pubmed_id": "33327438", "title": null }, { - "PMCID": null, + "PMCID": "PMC5433619", "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.mehy.2016.08.013", + "pubmed_id": "27692168", "title": null }, { - "PMCID": null, + "PMCID": "PMC6774504", "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, + "doi": "10.1371/journal.pone.0223302", + "pubmed_id": "31577826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3716967", "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-511x-12-98", + "pubmed_id": "23835113", "title": null }, { - "PMCID": null, + "PMCID": "PMC207567", "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, + "doi": "10.1128/mcb.23.21.7794-7808.2003", + "pubmed_id": "14560023", "title": null }, { "PMCID": null, "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, + "doi": "10.1139/apnm-2012-0261", + "pubmed_id": "23537027", "title": null }, { - "PMCID": null, + "PMCID": "PMC7028721", "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/s41420-020-0241-z", + "pubmed_id": "32123584", "title": null }, { - "PMCID": null, + "PMCID": "PMC3929745", "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, + "doi": "10.1210/en.2013-1667", + "pubmed_id": "24424052", "title": null }, { "PMCID": null, "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, + "doi": "10.1038/ki.2010.265", + "pubmed_id": "20686447", "title": null }, { "PMCID": null, "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.3029864", + "pubmed_id": "3029864", "title": null }, { - "PMCID": null, + "PMCID": "PMC6718297", "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.abb.2019.108072", + "pubmed_id": "31422074", "title": null }, { - "PMCID": null, + "PMCID": "PMC6139518", "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, + "doi": "10.1152/ajprenal.00495.2017", + "pubmed_id": "29631357", "title": null }, { - "PMCID": null, + "PMCID": "PMC8868548", "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, + "doi": "10.3390/antiox11020179", + "pubmed_id": "35204062", "title": null }, { - "PMCID": null, + "PMCID": "PMC6787918", "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, + "doi": "10.1126/science.aav3722", + "pubmed_id": "31273070", "title": null }, { - "PMCID": null, + "PMCID": "PMC5960540", "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, + "doi": "10.1155/2018/7464702", + "pubmed_id": "29853792", "title": null }, { - "PMCID": null, + "PMCID": "PMC8751875", "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, + "doi": "10.1161/jaha.121.021212", + "pubmed_id": "34622671", "title": null } ], @@ -4130,7 +3654,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", + "doi": "10.3390/metabo13070842", "grants": [ "P42 ES007380", "P42ES007380", @@ -4162,35 +3686,35 @@ "PMCID": null, "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", "doi": null, - "pubmed_id": null, + "pubmed_id": "30212065", "title": null }, { "PMCID": null, "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { - "PMCID": null, + "PMCID": "PMC4792175", "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, + "doi": "10.1038/sdata.2016.18", + "pubmed_id": "26978244", "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { - "PMCID": null, + "PMCID": "PMC4702780", "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, + "doi": "10.1093/nar/gkv1042", + "pubmed_id": "26467476", "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, { - "PMCID": null, + "PMCID": "PMC7145518", "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, + "doi": "10.1093/nar/gkz1019", + "pubmed_id": "31691833", "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" }, { @@ -4203,36 +3727,36 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { - "PMCID": null, + "PMCID": "PMC8000456", "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, + "doi": "10.3390/metabo11030163", + "pubmed_id": "33808985", "title": null }, { - "PMCID": null, + "PMCID": "PMC10364356", "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, + "doi": "10.1101/2022.03.04.483070", + "pubmed_id": "37482620", "title": null }, { - "PMCID": null, + "PMCID": "PMC3531110", "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, + "doi": "10.1093/nar/gks1004", + "pubmed_id": "23109552", "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { - "PMCID": null, + "PMCID": "PMC3638156", "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, + "doi": "10.1093/database/bat029", + "pubmed_id": "23630246", "title": "The MetaboLights repository: Curation challenges in metabolomics" }, { @@ -4245,7 +3769,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4287,15 +3811,15 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/mcse.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { - "PMCID": null, + "PMCID": "PMC5910482", "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, + "doi": "10.1007/s11306-018-1356-6", + "pubmed_id": "29706851", "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, { diff --git a/tests/testing_files/intermediate_results/author_search/no_PubMed/publication_dict.json b/tests/testing_files/intermediate_results/author_search/no_PubMed/publication_dict.json index 7d8be7a..6077fda 100644 --- a/tests/testing_files/intermediate_results/author_search/no_PubMed/publication_dict.json +++ b/tests/testing_files/intermediate_results/author_search/no_PubMed/publication_dict.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -212,21 +213,21 @@ { "PMCID": null, "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom, A. L. et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS). Sci. Total Envir. 778, 146192 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen, T. et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 1172, 122653 (2021).", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -240,98 +241,98 @@ { "PMCID": null, "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton, S. E. et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 40, 606\u2013630 (2021).", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk, K. H., Darlington, R., Benotti, M., Deeb, R. & Hawley, E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 204, 757\u2013764 (2017).", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. https://doi.org/10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman, M. F., Peldszus, S. & Anderson, W. B. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 50, 318\u2013340 (2014).", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva, A. O. et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 40, 631\u2013657 (2021).", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen, G. W. et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 157, 87\u201395 (2017).", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo, J. L. & Nadal, M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 177, 108648\u2013108648 (2019).", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn, E. et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 248, 101\u2013113 (2019).", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai, X. & Son, Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 751, 141622\u2013141622 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li, Y. et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 216, 118295\u2013118295 (2022).", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale, S. E. et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 171, 9\u201318 (2017).", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber, J. L. et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 9, 530\u2013541 (2007).", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -345,28 +346,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9, M. A. et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 55, 5848\u20135856 (2021).", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson, D. T. et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 54, 15768\u201315777 (2020).", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan, J. et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 31, 7\u201326 (2021).", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -380,42 +381,42 @@ { "PMCID": null, "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu, X. C. et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 3, 344\u2013350 (2016).", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -429,21 +430,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka, \u00c1., Szer\u00e9nyi, Z. M., Sz\u00e9chy, A. & Kocsis, T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 48, 126\u2013138 (2013).", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo, J. L. & Adamson, D. T. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 236, 505\u2013513 (2018).", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -522,14 +523,14 @@ { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -557,63 +558,63 @@ { "PMCID": null, "citation": "Protein Data Bank. the single global archive for 3D macromolecular structure data. Nucleic acids research 47, D520\u2013D528 (2019).", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud, M. et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research 44, D463\u2013D470 (2016).", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma, A. et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics 29, 365\u2013371 (2001).", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -634,21 +635,21 @@ { "PMCID": null, "citation": "Kinkade, D. & Shepherd, A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal 9, 177\u2013186 (2022).", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo, A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science 36, 1059\u20131099 (2022).", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -662,14 +663,14 @@ { "PMCID": null, "citation": "Sicilia, M.-A., Garc\u00eda-Barriocanal, E. & S\u00e1nchez-Alonso, S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science 106, 54\u201360 (2017).", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -683,7 +684,7 @@ { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -697,21 +698,21 @@ { "PMCID": null, "citation": "Thompson, P. T., Powell, C. D. & Moseley, H. N. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one 17, e0277834 (2022).", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -732,14 +733,14 @@ { "PMCID": null, "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -794,14 +795,15 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 4, + "month": 3, "year": 2023 }, "pubmed_id": null, "queried_sources": [ "Google Scholar", - "Crossref" + "Crossref", + "ORCID" ], "references": [ { @@ -814,21 +816,21 @@ { "PMCID": null, "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u201351.", - "doi": "https://doi.org/10.1002/pro.3715", + "doi": "10.1002/pro.3715", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u201351.", - "doi": "https://doi.org/10.1093/nar/gkaa970", + "doi": "10.1093/nar/gkaa970", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", "pubmed_id": null, "title": null }, @@ -849,7 +851,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -870,7 +872,7 @@ { "PMCID": null, "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, @@ -884,14 +886,14 @@ { "PMCID": null, "citation": "Castelli FM. KEGGutils v04.1. Computer software. 2022. Zenodo. https://doi.org/10.5281/zenodo.7482523.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", + "doi": "10.1093/bioinformatics/btp163", "pubmed_id": null, "title": null }, @@ -960,35 +962,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u201370.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u20136.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -1030,14 +1032,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. https://doi.org/10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", + "doi": "10.1016/j.cbpa.2016.12.024", "pubmed_id": null, "title": null }, @@ -1051,7 +1053,7 @@ { "PMCID": null, "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", + "doi": "10.1093/gigascience/giab060", "pubmed_id": null, "title": null }, @@ -1065,14 +1067,14 @@ { "PMCID": null, "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u201384.", - "doi": "https://doi.org/10.1107/S0021889809008784", + "doi": "10.1107/S0021889809008784", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u20133.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -1150,7 +1152,7 @@ "methods": null, "publication_date": { "day": null, - "month": null, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -1162,7 +1164,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, @@ -1176,7 +1178,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, @@ -1204,21 +1206,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, @@ -1232,28 +1234,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "doi": "10.1371/journal.pbio.2006930", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", + "doi": "10.1038/nbt.1411", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, @@ -1281,28 +1283,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", + "doi": "10.1038/ng.1054", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", + "doi": "10.1089/omi.2008.0019", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", + "doi": "10.1089/omi.2006.10.164", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", + "doi": "10.4056/sigs.147362", "pubmed_id": null, "title": null }, @@ -1316,35 +1318,35 @@ { "PMCID": null, "citation": "Gamble M Goble C Klyne G Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago Illinois 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", + "doi": "10.1289/EHP10092", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", + "doi": "10.3389/frai.2020.00031", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", + "doi": "10.1093/toxsci/kfm090", "pubmed_id": null, "title": null }, @@ -1372,7 +1374,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", + "doi": "10.1016/j.comtox.2019.100096", "pubmed_id": null, "title": null }, @@ -1386,7 +1388,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", + "doi": "10.1093/nar/gkz1019", "pubmed_id": null, "title": null }, @@ -1400,119 +1402,119 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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"doi": "https://doi.org/10.1002/mas.20108", + "doi": "10.1002/mas.20108", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "doi": "10.1016/j.aca.2017.04.014", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "doi": "10.1021/ac3018795", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "doi": "10.1021/ac1011574", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "doi": "10.1016/j.pharmthera.2011.12.007", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "doi": "10.1186/1741-7007-9-37", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "doi": "10.1172/JCI72873", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -2211,7 +2213,7 @@ { "PMCID": null, "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -2253,14 +2255,14 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, @@ -2330,19 +2332,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -2363,19 +2366,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs3.json b/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs3.json index 7d8be7a..aab9254 100644 --- a/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs3.json +++ b/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs3.json @@ -212,21 +212,21 @@ { "PMCID": null, "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom, A. L. et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS). Sci. Total Envir. 778, 146192 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen, T. et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 1172, 122653 (2021).", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -240,98 +240,98 @@ { "PMCID": null, "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton, S. E. et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 40, 606\u2013630 (2021).", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk, K. H., Darlington, R., Benotti, M., Deeb, R. & Hawley, E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 204, 757\u2013764 (2017).", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. https://doi.org/10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman, M. F., Peldszus, S. & Anderson, W. B. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 50, 318\u2013340 (2014).", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva, A. O. et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 40, 631\u2013657 (2021).", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen, G. W. et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 157, 87\u201395 (2017).", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo, J. L. & Nadal, M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 177, 108648\u2013108648 (2019).", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn, E. et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 248, 101\u2013113 (2019).", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai, X. & Son, Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 751, 141622\u2013141622 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li, Y. et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 216, 118295\u2013118295 (2022).", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale, S. E. et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 171, 9\u201318 (2017).", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber, J. L. et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 9, 530\u2013541 (2007).", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -345,28 +345,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9, M. A. et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 55, 5848\u20135856 (2021).", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson, D. T. et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 54, 15768\u201315777 (2020).", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan, J. et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 31, 7\u201326 (2021).", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -380,42 +380,42 @@ { "PMCID": null, "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu, X. C. et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 3, 344\u2013350 (2016).", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -429,21 +429,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka, \u00c1., Szer\u00e9nyi, Z. M., Sz\u00e9chy, A. & Kocsis, T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 48, 126\u2013138 (2013).", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo, J. L. & Adamson, D. T. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 236, 505\u2013513 (2018).", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -522,14 +522,14 @@ { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -557,63 +557,63 @@ { "PMCID": null, "citation": "Protein Data Bank. the single global archive for 3D macromolecular structure data. Nucleic acids research 47, D520\u2013D528 (2019).", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud, M. et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research 44, D463\u2013D470 (2016).", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma, A. et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics 29, 365\u2013371 (2001).", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -634,21 +634,21 @@ { "PMCID": null, "citation": "Kinkade, D. & Shepherd, A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal 9, 177\u2013186 (2022).", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo, A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science 36, 1059\u20131099 (2022).", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -662,14 +662,14 @@ { "PMCID": null, "citation": "Sicilia, M.-A., Garc\u00eda-Barriocanal, E. & S\u00e1nchez-Alonso, S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science 106, 54\u201360 (2017).", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -683,7 +683,7 @@ { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -697,21 +697,21 @@ { "PMCID": null, "citation": "Thompson, P. T., Powell, C. D. & Moseley, H. N. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one 17, e0277834 (2022).", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -732,14 +732,14 @@ { "PMCID": null, "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -794,8 +794,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 4, + "month": 3, "year": 2023 }, "pubmed_id": null, @@ -814,21 +814,21 @@ { "PMCID": null, "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u201351.", - "doi": "https://doi.org/10.1002/pro.3715", + "doi": "10.1002/pro.3715", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u201351.", - "doi": "https://doi.org/10.1093/nar/gkaa970", + "doi": "10.1093/nar/gkaa970", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", "pubmed_id": null, "title": null }, @@ -849,7 +849,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -870,7 +870,7 @@ { "PMCID": null, "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, @@ -884,14 +884,14 @@ { "PMCID": null, "citation": "Castelli FM. KEGGutils v04.1. Computer software. 2022. Zenodo. https://doi.org/10.5281/zenodo.7482523.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", + "doi": "10.1093/bioinformatics/btp163", "pubmed_id": null, "title": null }, @@ -960,35 +960,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u201370.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u20136.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -1030,14 +1030,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. https://doi.org/10.6084/m9.figshare.19221159. 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J Appl Crystallogr. 2009;42(3):376\u201384.", - "doi": "https://doi.org/10.1107/S0021889809008784", + "doi": "10.1107/S0021889809008784", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u20133.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -1150,7 +1150,7 @@ "methods": null, "publication_date": { "day": null, - "month": null, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -1162,7 +1162,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, @@ -1176,7 +1176,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, @@ -1204,21 +1204,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, @@ -1232,28 +1232,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "doi": "10.1371/journal.pbio.2006930", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", + "doi": "10.1038/nbt.1411", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, @@ -1281,28 +1281,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", + "doi": "10.1038/ng.1054", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", + "doi": "10.1089/omi.2008.0019", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", + "doi": "10.1089/omi.2006.10.164", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", + "doi": "10.4056/sigs.147362", "pubmed_id": null, "title": null }, @@ -1316,35 +1316,35 @@ { "PMCID": null, "citation": "Gamble M Goble C Klyne G Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago Illinois 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", + "doi": "10.1289/EHP10092", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", + "doi": "10.3389/frai.2020.00031", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", + "doi": "10.1093/toxsci/kfm090", "pubmed_id": null, "title": null }, @@ -1372,7 +1372,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", + "doi": "10.1016/j.comtox.2019.100096", "pubmed_id": null, "title": null }, @@ -1386,7 +1386,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", + "doi": "10.1093/nar/gkz1019", "pubmed_id": null, "title": null }, @@ -1400,119 +1400,119 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -2211,7 +2211,7 @@ { "PMCID": null, "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -2253,14 +2253,14 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, diff --git a/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs4.json b/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs4.json index 7d8be7a..6077fda 100644 --- a/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs4.json +++ b/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs4.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -212,21 +213,21 @@ { "PMCID": null, "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom, A. L. et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS). Sci. Total Envir. 778, 146192 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen, T. et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 1172, 122653 (2021).", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -240,98 +241,98 @@ { "PMCID": null, "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton, S. E. et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 40, 606\u2013630 (2021).", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk, K. H., Darlington, R., Benotti, M., Deeb, R. & Hawley, E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 204, 757\u2013764 (2017).", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. https://doi.org/10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman, M. F., Peldszus, S. & Anderson, W. B. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 50, 318\u2013340 (2014).", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva, A. O. et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 40, 631\u2013657 (2021).", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen, G. W. et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 157, 87\u201395 (2017).", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo, J. L. & Nadal, M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 177, 108648\u2013108648 (2019).", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn, E. et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 248, 101\u2013113 (2019).", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai, X. & Son, Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 751, 141622\u2013141622 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li, Y. et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 216, 118295\u2013118295 (2022).", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale, S. E. et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 171, 9\u201318 (2017).", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber, J. L. et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 9, 530\u2013541 (2007).", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -345,28 +346,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9, M. A. et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 55, 5848\u20135856 (2021).", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson, D. T. et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 54, 15768\u201315777 (2020).", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan, J. et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 31, 7\u201326 (2021).", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -380,42 +381,42 @@ { "PMCID": null, "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu, X. C. et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 3, 344\u2013350 (2016).", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -429,21 +430,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka, \u00c1., Szer\u00e9nyi, Z. M., Sz\u00e9chy, A. & Kocsis, T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 48, 126\u2013138 (2013).", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo, J. L. & Adamson, D. T. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 236, 505\u2013513 (2018).", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -522,14 +523,14 @@ { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -557,63 +558,63 @@ { "PMCID": null, "citation": "Protein Data Bank. the single global archive for 3D macromolecular structure data. Nucleic acids research 47, D520\u2013D528 (2019).", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud, M. et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research 44, D463\u2013D470 (2016).", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma, A. et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics 29, 365\u2013371 (2001).", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -634,21 +635,21 @@ { "PMCID": null, "citation": "Kinkade, D. & Shepherd, A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal 9, 177\u2013186 (2022).", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo, A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science 36, 1059\u20131099 (2022).", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -662,14 +663,14 @@ { "PMCID": null, "citation": "Sicilia, M.-A., Garc\u00eda-Barriocanal, E. & S\u00e1nchez-Alonso, S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science 106, 54\u201360 (2017).", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -683,7 +684,7 @@ { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -697,21 +698,21 @@ { "PMCID": null, "citation": "Thompson, P. T., Powell, C. D. & Moseley, H. N. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one 17, e0277834 (2022).", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -732,14 +733,14 @@ { "PMCID": null, "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -794,14 +795,15 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 4, + "month": 3, "year": 2023 }, "pubmed_id": null, "queried_sources": [ "Google Scholar", - "Crossref" + "Crossref", + "ORCID" ], "references": [ { @@ -814,21 +816,21 @@ { "PMCID": null, "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u201351.", - "doi": "https://doi.org/10.1002/pro.3715", + "doi": "10.1002/pro.3715", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u201351.", - "doi": "https://doi.org/10.1093/nar/gkaa970", + "doi": "10.1093/nar/gkaa970", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", "pubmed_id": null, "title": null }, @@ -849,7 +851,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -870,7 +872,7 @@ { "PMCID": null, "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, @@ -884,14 +886,14 @@ { "PMCID": null, "citation": "Castelli FM. KEGGutils v04.1. Computer software. 2022. Zenodo. https://doi.org/10.5281/zenodo.7482523.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", + "doi": "10.1093/bioinformatics/btp163", "pubmed_id": null, "title": null }, @@ -960,35 +962,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u201370.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u20136.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -1030,14 +1032,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. https://doi.org/10.6084/m9.figshare.19221159. 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Nucleic Acid Res. 2007;35(suppl1):D301\u20133.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -1150,7 +1152,7 @@ "methods": null, "publication_date": { "day": null, - "month": null, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -1162,7 +1164,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, @@ -1176,7 +1178,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, @@ -1204,21 +1206,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, @@ -1232,28 +1234,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "doi": "10.1371/journal.pbio.2006930", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", + "doi": "10.1038/nbt.1411", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, @@ -1281,28 +1283,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", + "doi": "10.1038/ng.1054", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", + "doi": "10.1089/omi.2008.0019", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", + "doi": "10.1089/omi.2006.10.164", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", + "doi": "10.4056/sigs.147362", "pubmed_id": null, "title": null }, @@ -1316,35 +1318,35 @@ { "PMCID": null, "citation": "Gamble M Goble C Klyne G Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago Illinois 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", + "doi": "10.1289/EHP10092", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", + "doi": "10.3389/frai.2020.00031", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", + "doi": "10.1093/toxsci/kfm090", "pubmed_id": null, "title": null }, @@ -1372,7 +1374,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", + "doi": "10.1016/j.comtox.2019.100096", "pubmed_id": null, "title": null }, @@ -1386,7 +1388,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", + "doi": "10.1093/nar/gkz1019", "pubmed_id": null, "title": null }, @@ -1400,119 +1402,119 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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"doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { "PMCID": null, "citation": "Powell, C.D., and Moseley, H.N. (2021). The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites, 11.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C.D., and Moseley, H.N. (2022). The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -2211,7 +2213,7 @@ { "PMCID": null, "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -2253,14 +2255,14 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, @@ -2330,19 +2332,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -2363,19 +2366,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs5.json b/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs5.json index 7d8be7a..6077fda 100644 --- a/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs5.json +++ b/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs5.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -212,21 +213,21 @@ { "PMCID": null, "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom, A. L. et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS). Sci. Total Envir. 778, 146192 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen, T. et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 1172, 122653 (2021).", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -240,98 +241,98 @@ { "PMCID": null, "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton, S. E. et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 40, 606\u2013630 (2021).", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk, K. H., Darlington, R., Benotti, M., Deeb, R. & Hawley, E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 204, 757\u2013764 (2017).", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. https://doi.org/10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman, M. F., Peldszus, S. & Anderson, W. B. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 50, 318\u2013340 (2014).", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva, A. O. et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 40, 631\u2013657 (2021).", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen, G. W. et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 157, 87\u201395 (2017).", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo, J. L. & Nadal, M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 177, 108648\u2013108648 (2019).", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn, E. et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 248, 101\u2013113 (2019).", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai, X. & Son, Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 751, 141622\u2013141622 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li, Y. et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 216, 118295\u2013118295 (2022).", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale, S. E. et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 171, 9\u201318 (2017).", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber, J. L. et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 9, 530\u2013541 (2007).", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -345,28 +346,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9, M. A. et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 55, 5848\u20135856 (2021).", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson, D. T. et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 54, 15768\u201315777 (2020).", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan, J. et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 31, 7\u201326 (2021).", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -380,42 +381,42 @@ { "PMCID": null, "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu, X. C. et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 3, 344\u2013350 (2016).", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -429,21 +430,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka, \u00c1., Szer\u00e9nyi, Z. M., Sz\u00e9chy, A. & Kocsis, T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 48, 126\u2013138 (2013).", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo, J. L. & Adamson, D. T. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 236, 505\u2013513 (2018).", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -522,14 +523,14 @@ { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -557,63 +558,63 @@ { "PMCID": null, "citation": "Protein Data Bank. the single global archive for 3D macromolecular structure data. Nucleic acids research 47, D520\u2013D528 (2019).", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud, M. et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research 44, D463\u2013D470 (2016).", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma, A. et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics 29, 365\u2013371 (2001).", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -634,21 +635,21 @@ { "PMCID": null, "citation": "Kinkade, D. & Shepherd, A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal 9, 177\u2013186 (2022).", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo, A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science 36, 1059\u20131099 (2022).", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -662,14 +663,14 @@ { "PMCID": null, "citation": "Sicilia, M.-A., Garc\u00eda-Barriocanal, E. & S\u00e1nchez-Alonso, S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science 106, 54\u201360 (2017).", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -683,7 +684,7 @@ { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -697,21 +698,21 @@ { "PMCID": null, "citation": "Thompson, P. T., Powell, C. D. & Moseley, H. N. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one 17, e0277834 (2022).", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -732,14 +733,14 @@ { "PMCID": null, "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -794,14 +795,15 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 4, + "month": 3, "year": 2023 }, "pubmed_id": null, "queried_sources": [ "Google Scholar", - "Crossref" + "Crossref", + "ORCID" ], "references": [ { @@ -814,21 +816,21 @@ { "PMCID": null, "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u201351.", - "doi": "https://doi.org/10.1002/pro.3715", + "doi": "10.1002/pro.3715", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u201351.", - "doi": "https://doi.org/10.1093/nar/gkaa970", + "doi": "10.1093/nar/gkaa970", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", "pubmed_id": null, "title": null }, @@ -849,7 +851,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -870,7 +872,7 @@ { "PMCID": null, "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, @@ -884,14 +886,14 @@ { "PMCID": null, "citation": "Castelli FM. KEGGutils v04.1. Computer software. 2022. Zenodo. https://doi.org/10.5281/zenodo.7482523.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", + "doi": "10.1093/bioinformatics/btp163", "pubmed_id": null, "title": null }, @@ -960,35 +962,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u201370.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u20136.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -1030,14 +1032,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. https://doi.org/10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", + "doi": "10.1016/j.cbpa.2016.12.024", "pubmed_id": null, "title": null }, @@ -1051,7 +1053,7 @@ { "PMCID": null, "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", + "doi": "10.1093/gigascience/giab060", "pubmed_id": null, "title": null }, @@ -1065,14 +1067,14 @@ { "PMCID": null, "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u201384.", - "doi": "https://doi.org/10.1107/S0021889809008784", + "doi": "10.1107/S0021889809008784", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u20133.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -1150,7 +1152,7 @@ "methods": null, "publication_date": { "day": null, - "month": null, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -1162,7 +1164,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, @@ -1176,7 +1178,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, @@ -1204,21 +1206,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, @@ -1232,28 +1234,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "doi": "10.1371/journal.pbio.2006930", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", + "doi": "10.1038/nbt.1411", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, @@ -1281,28 +1283,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", + "doi": "10.1038/ng.1054", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", + "doi": "10.1089/omi.2008.0019", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", + "doi": "10.1089/omi.2006.10.164", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", + "doi": "10.4056/sigs.147362", "pubmed_id": null, "title": null }, @@ -1316,35 +1318,35 @@ { "PMCID": null, "citation": "Gamble M Goble C Klyne G Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago Illinois 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", + "doi": "10.1289/EHP10092", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", + "doi": "10.3389/frai.2020.00031", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", + "doi": "10.1093/toxsci/kfm090", "pubmed_id": null, "title": null }, @@ -1372,7 +1374,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", + "doi": "10.1016/j.comtox.2019.100096", "pubmed_id": null, "title": null }, @@ -1386,7 +1388,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", + "doi": "10.1093/nar/gkz1019", "pubmed_id": null, "title": null }, @@ -1400,119 +1402,119 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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(2021). The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites, 11.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C.D., and Moseley, H.N. (2022). The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -2211,7 +2213,7 @@ { "PMCID": null, "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -2253,14 +2255,14 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, @@ -2330,19 +2332,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -2363,19 +2366,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs6.json b/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs6.json index 7d8be7a..6077fda 100644 --- a/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs6.json +++ b/tests/testing_files/intermediate_results/author_search/no_PubMed/running_pubs6.json @@ -47,19 +47,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.26434/chemrxiv-2022-bt3f6", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 25, + "month": 7, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -212,21 +213,21 @@ { "PMCID": null, "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom, A. L. et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS). Sci. Total Envir. 778, 146192 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen, T. et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 1172, 122653 (2021).", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -240,98 +241,98 @@ { "PMCID": null, "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton, S. E. et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 40, 606\u2013630 (2021).", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk, K. H., Darlington, R., Benotti, M., Deeb, R. & Hawley, E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 204, 757\u2013764 (2017).", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. https://doi.org/10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman, M. F., Peldszus, S. & Anderson, W. B. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 50, 318\u2013340 (2014).", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva, A. O. et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 40, 631\u2013657 (2021).", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen, G. W. et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 157, 87\u201395 (2017).", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo, J. L. & Nadal, M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 177, 108648\u2013108648 (2019).", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn, E. et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 248, 101\u2013113 (2019).", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai, X. & Son, Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 751, 141622\u2013141622 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li, Y. et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 216, 118295\u2013118295 (2022).", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale, S. E. et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 171, 9\u201318 (2017).", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber, J. L. et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 9, 530\u2013541 (2007).", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -345,28 +346,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9, M. A. et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 55, 5848\u20135856 (2021).", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson, D. T. et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 54, 15768\u201315777 (2020).", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan, J. et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 31, 7\u201326 (2021).", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -380,42 +381,42 @@ { "PMCID": null, "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu, X. C. et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 3, 344\u2013350 (2016).", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -429,21 +430,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka, \u00c1., Szer\u00e9nyi, Z. M., Sz\u00e9chy, A. & Kocsis, T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 48, 126\u2013138 (2013).", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo, J. L. & Adamson, D. T. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 236, 505\u2013513 (2018).", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -522,14 +523,14 @@ { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -557,63 +558,63 @@ { "PMCID": null, "citation": "Protein Data Bank. the single global archive for 3D macromolecular structure data. Nucleic acids research 47, D520\u2013D528 (2019).", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud, M. et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research 44, D463\u2013D470 (2016).", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma, A. et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics 29, 365\u2013371 (2001).", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -634,21 +635,21 @@ { "PMCID": null, "citation": "Kinkade, D. & Shepherd, A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal 9, 177\u2013186 (2022).", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo, A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science 36, 1059\u20131099 (2022).", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -662,14 +663,14 @@ { "PMCID": null, "citation": "Sicilia, M.-A., Garc\u00eda-Barriocanal, E. & S\u00e1nchez-Alonso, S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science 106, 54\u201360 (2017).", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -683,7 +684,7 @@ { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -697,21 +698,21 @@ { "PMCID": null, "citation": "Thompson, P. T., Powell, C. D. & Moseley, H. N. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one 17, e0277834 (2022).", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -732,14 +733,14 @@ { "PMCID": null, "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -794,14 +795,15 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 4, + "month": 3, "year": 2023 }, "pubmed_id": null, "queried_sources": [ "Google Scholar", - "Crossref" + "Crossref", + "ORCID" ], "references": [ { @@ -814,21 +816,21 @@ { "PMCID": null, "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u201351.", - "doi": "https://doi.org/10.1002/pro.3715", + "doi": "10.1002/pro.3715", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u201351.", - "doi": "https://doi.org/10.1093/nar/gkaa970", + "doi": "10.1093/nar/gkaa970", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", "pubmed_id": null, "title": null }, @@ -849,7 +851,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -870,7 +872,7 @@ { "PMCID": null, "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, @@ -884,14 +886,14 @@ { "PMCID": null, "citation": "Castelli FM. KEGGutils v04.1. Computer software. 2022. Zenodo. https://doi.org/10.5281/zenodo.7482523.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", + "doi": "10.1093/bioinformatics/btp163", "pubmed_id": null, "title": null }, @@ -960,35 +962,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u201370.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u20136.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -1030,14 +1032,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. https://doi.org/10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", + "doi": "10.1016/j.cbpa.2016.12.024", "pubmed_id": null, "title": null }, @@ -1051,7 +1053,7 @@ { "PMCID": null, "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", + "doi": "10.1093/gigascience/giab060", "pubmed_id": null, "title": null }, @@ -1065,14 +1067,14 @@ { "PMCID": null, "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u201384.", - "doi": "https://doi.org/10.1107/S0021889809008784", + "doi": "10.1107/S0021889809008784", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u20133.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -1150,7 +1152,7 @@ "methods": null, "publication_date": { "day": null, - "month": null, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -1162,7 +1164,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, @@ -1176,7 +1178,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, @@ -1204,21 +1206,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, @@ -1232,28 +1234,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "doi": "10.1371/journal.pbio.2006930", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", + "doi": "10.1038/nbt.1411", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, @@ -1281,28 +1283,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", + "doi": "10.1038/ng.1054", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", + "doi": "10.1089/omi.2008.0019", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", + "doi": "10.1089/omi.2006.10.164", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", + "doi": "10.4056/sigs.147362", "pubmed_id": null, "title": null }, @@ -1316,35 +1318,35 @@ { "PMCID": null, "citation": "Gamble M Goble C Klyne G Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago Illinois 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", + "doi": "10.1289/EHP10092", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", + "doi": "10.3389/frai.2020.00031", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", + "doi": "10.1093/toxsci/kfm090", "pubmed_id": null, "title": null }, @@ -1372,7 +1374,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", + "doi": "10.1016/j.comtox.2019.100096", "pubmed_id": null, "title": null }, @@ -1386,7 +1388,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", + "doi": "10.1093/nar/gkz1019", "pubmed_id": null, "title": null }, @@ -1400,119 +1402,119 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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(2021). The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites, 11.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C.D., and Moseley, H.N. (2022). The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -2211,7 +2213,7 @@ { "PMCID": null, "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -2253,14 +2255,14 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, @@ -2330,19 +2332,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.02.24.481854", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 28, + "month": 2, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, @@ -2363,19 +2366,20 @@ ], "conclusions": null, "copyrights": null, - "doi": null, + "doi": "10.1101/2022.12.08.519680", "grants": [], "journal": null, "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 12, + "month": 12, "year": 2022 }, "pubmed_id": null, "queried_sources": [ - "Google Scholar" + "Google Scholar", + "ORCID" ], "references": [], "results": null, diff --git a/tests/testing_files/intermediate_results/ref_search/all/matching_key_for_citation1.json b/tests/testing_files/intermediate_results/ref_search/all/matching_key_for_citation1.json index 934664a..29742f5 100644 --- a/tests/testing_files/intermediate_results/ref_search/all/matching_key_for_citation1.json +++ b/tests/testing_files/intermediate_results/ref_search/all/matching_key_for_citation1.json @@ -1,5 +1,5 @@ [ - null, + "https://doi.org/10.3390/metabo3040853", null, "https://doi.org/10.1007/978-1-4939-1258-2_11" ] \ No newline at end of file diff --git a/tests/testing_files/intermediate_results/ref_search/all/publication_dict.json b/tests/testing_files/intermediate_results/ref_search/all/publication_dict.json index 78f68b2..ebb1d78 100644 --- a/tests/testing_files/intermediate_results/ref_search/all/publication_dict.json +++ b/tests/testing_files/intermediate_results/ref_search/all/publication_dict.json @@ -46,7 +46,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "doi": "10.1007/978-1-4939-1258-2_11", "grants": [ "1R01CA118434-01A2", "5P20RR018733", @@ -79,14 +79,14 @@ "PMCID": null, "citation": "Schlotterbeck G, Ross A, Dieterle F, Senn H. Metabolic profiling technologies for biomarker discovery in biomedicine and drug development. Pharmacogenomics. 2006;7:1055\u20131075.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17054416", "title": null }, { "PMCID": null, "citation": "Oresic M, Vidal-Puig A, Hanninen V. Metabolomic approaches to phenotype characterization and applications to complex diseases. Expert Review of Molecular Diagnostics. 2006;6:575\u2013585.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16824031", "title": null }, { @@ -97,24 +97,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2724746", "citation": "Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457:910\u2013914.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19212411", "title": null }, { "PMCID": null, "citation": "Griffiths William J., T. K., Wang Yuqin, Kohl Matthias, Enot David P., Deigner H-P. Targeted Metabolomics for Biomarker Discovery. Angew. Chem. Int. Ed. 2010;49:5426\u20135446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20629054", "title": null }, { "PMCID": null, "citation": "Theodoridis G, Gika HG, Wilson ID. Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies. Mass Spectrom. Rev. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "21384411", "title": null }, { @@ -128,14 +128,14 @@ "PMCID": null, "citation": "Andrew Clayton T, Lindon JC, Cloarec O, Antti H, Charuel C, Hanton G, Provost J-P, Le Net J-L\u00d8, Baker D, Walley RJ, Everett JR, Nicholson JK. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature. 2006;440:1073\u20131077.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16625200", "title": null }, { "PMCID": null, "citation": "Harrigan GG, Brackett DJ, Boros LG. Medicinal chemistry, metabolic profiling and drug target discovery: A role for metabolic profiling in reverse pharmacology and chemical genetics. Mini-Reviews in Medicinal Chemistry. 2005;5:13\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15638788", "title": null }, { @@ -149,133 +149,133 @@ "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN. Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metab. Rev. 2006;38:707\u2013732.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17145697", "title": null }, { "PMCID": null, "citation": "Robertson DG. Metabonomics in toxicology: A review. Toxicological Sciences. 2005;85:809\u2013822.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15689416", "title": null }, { "PMCID": null, "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15544433", "title": null }, { - "PMCID": null, + "PMCID": "PMC2140249", "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17786640", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { "PMCID": null, "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19478804", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21466455", "title": null }, { - "PMCID": null, + "PMCID": "PMC3087304", "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21350847", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { "PMCID": null, "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16258367", "title": null }, { "PMCID": null, "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15611129", "title": null }, { - "PMCID": null, + "PMCID": "PMC2917841", "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20686576", "title": null }, { "PMCID": null, "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15663322", "title": null }, { @@ -286,122 +286,122 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM)) Molecular Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley HNB. Error Analysis and Propagation in Metabolomics Data Analysis. Comp Struct Biotech J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN, Jardetzky O. Combined use of proton NMR and gas chromatography-mass spectra for metabolite monitoring and in vivo proton NMR assignments. Biochimica et Biophysica Acta. 1986;882:154\u2013167.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3011112", "title": null }, { "PMCID": null, "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "11062433", "title": null }, { - "PMCID": null, + "PMCID": "PMC3746802", "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22608776", "title": null }, { - "PMCID": null, + "PMCID": "PMC3430598", "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study. BMC Genomics. 2012;13:334.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22823888", "title": null }, { - "PMCID": null, + "PMCID": "PMC3384197", "citation": "Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, Phang JM. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci U S A. 2012;109:8983\u20138988.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22615405", "title": null }, { - "PMCID": null, + "PMCID": "PMC3703516", "citation": "Dong C, Yuan T, Wu Y, Wang Y, Fan TW, Miriyala S, Lin Y, Yao J, Shi J, Kang T, Lorkiewicz P, St Clair D, Hung MC, Evers BM, Zhou BP. Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 2013;23:316\u2013331.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23453623", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2475696", "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18364355", "title": null }, { "PMCID": null, "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15994921", "title": null }, { "PMCID": null, "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9612242", "title": null }, { "PMCID": null, "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16317166", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { "PMCID": null, "citation": "Yang TH, Wittmann C, Heinzle E. Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum. Metab Eng. 2006;8:432\u2013446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16750927", "title": null }, { - "PMCID": null, + "PMCID": "PMC2952699", "citation": "Paul Lee W-N, P. N. W., Xuc Jun, Liang Go Vay. Tracer-based Metabolomics: Concepts and Practices. Clinical Biochemistry. 2010;43:1269\u20131277.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20713038", "title": null }, { @@ -419,38 +419,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TW, Lorkiewicz P, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol Ther. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Fan TWM, Colmer TD, Lane AN, Higashi RM. Determination of Metabolites by Proton Nmr and Gc Analysis for Organic Osmolytes in Crude Tissue Extracts. Analytical Biochemistry. 1993;214:260\u2013271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8250233", "title": null }, { "PMCID": null, "citation": "Gradwell MJ, Fan TWM, Lane AN. Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional 1H-31P NMR heteronuclear total correlation spectroscopy (hetero TOCSY) Analytical Biochemistry. 1998;263:139\u2013149.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9799525", "title": null }, { @@ -475,17 +475,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { - "PMCID": null, + "PMCID": "PMC3282107", "citation": "Yuneva MO, Fan TW-M, Higashi RM, Allen TA, Balakrishnan A, Goga A, Ferraris DV, Tsukamoto T, Wang C, Seo Y, Chen X, Bishop JM. The Metabolic Profile of Tumors Depends on Both the Responsible Genetic Lesion and Tissue Type Cell Metab. 2012;15:157\u2013170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22326218", "title": null }, { @@ -496,10 +496,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2847149", "citation": "Allwood JW, Erban A, de Koning S, Dunn WB, Luedemann A, Lommen A, Kay L, Loscher R, Kopka J, Goodacre R. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20376177", "title": null }, { @@ -513,91 +513,91 @@ "PMCID": null, "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16448047", "title": null }, { "PMCID": null, "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 2005;22:1155\u20131169.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16240456", "title": null }, { "PMCID": null, "citation": "Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, Goodacre R. Global Metabolic Profiling of Escherichia coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites. Anal. Chem. 2008;80:2939\u20132948.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18331064", "title": null }, { "PMCID": null, "citation": "Sellick CA, Hansen R, Maqsood AR, Dunn WB, Stephens GM, Goodacre R, Dickson AJ. Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells. Analytical Chemistry. 2009;81:174\u2013183.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19061395", "title": null }, { "PMCID": null, "citation": "Bolten CJ, Kiefer P, Letisse F, Portais JC, Wittmann C. Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17411014", "title": null }, { "PMCID": null, "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1514678", "title": null }, { "PMCID": null, "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12103361", "title": null }, { "PMCID": null, "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12009699", "title": null }, { "PMCID": null, "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17630720", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3501132", "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. Metabolomics. 2012 In press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23175637", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJ, Lorkiewicz PK, Higashi RM, Fan TW, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { @@ -608,45 +608,45 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane AN, Fan TW-M, Xie X, Moseley HN, Higashi RM. Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR Anal. Chim. Acta. 2009;651:201\u2013208.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz P, Higashi RM, Lane AN, Fan TWM. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8:930\u2013939.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8811175", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10863556", "title": null }, { - "PMCID": null, + "PMCID": "PMC1794290", "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A. 2007;104:1777\u20131782.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17267599", "title": null } ], @@ -698,8 +698,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 29, + "month": 9, "year": 2014 }, "pubmed_id": null, @@ -716,26 +716,26 @@ "authors": [ { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "William", - "initials": null, + "firstname": "William J", + "initials": "WJ", "lastname": "Carreer" }, { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "Robert", - "initials": null, + "firstname": "Robert M", + "initials": "RM", "lastname": "Flight" }, { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "Hunter", - "initials": null, + "firstname": "Hunter N B", + "initials": "HN", "lastname": "Moseley" } ], @@ -748,7 +748,7 @@ "R01 ES022191", "U24 DK097215" ], - "journal": "MDPI AG", + "journal": "Metabolites", "keywords": [ "Fourier transform mass spectrometry", "analytical derivation", @@ -761,164 +761,164 @@ "publication_date": { "day": 10, "month": 1, - "year": 2013 + "year": 2014 }, "pubmed_id": "24404440", "queried_sources": [ - "Crossref", - "PubMed" + "PubMed", + "Crossref" ], "references": [ { "PMCID": null, "citation": "Rittenberg D., Schoenheimer R. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1937;121:235.", - "doi": "https://doi.org/10.1016/S0021-9258(18)74342-1", + "doi": "10.1016/S0021-9258(18)74342-1", "pubmed_id": null, "title": "Deuterium as an indicator in the study of intermediary metabolism" }, { "PMCID": null, "citation": "Schoenheimer R., Rittenberg D. The study of intermediary metabolism of animals with the aid of isotopes. Physiol. Rev. 1940;20:218.", - "doi": "https://doi.org/10.1152/physrev.1940.20.2.218", + "doi": "10.1152/physrev.1940.20.2.218", "pubmed_id": null, "title": "The study of intermediary metabolism of animals with the aid of isotopes" }, { "PMCID": null, "citation": "Schoenheimer R., Rittenberg D. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1935;111:163.", - "doi": "https://doi.org/10.1016/S0021-9258(18)75075-8", + "doi": "10.1016/S0021-9258(18)75075-8", "pubmed_id": null, "title": "Deuterium as an indicator in the study of intermediary metabolism" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.2174/1568009033481769", - "pubmed_id": null, + "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1476-4598-8-41", - "pubmed_id": null, + "PMCID": "PMC2717907", + "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2009.08.032", - "pubmed_id": null, + "PMCID": "PMC2757635", + "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac061906b", - "pubmed_id": null, + "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/bp000058h", - "pubmed_id": null, + "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1046/j.1432-1033.2003.03448.x", - "pubmed_id": null, + "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", "title": null }, { "PMCID": null, "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10362629", "title": "Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bms.1200200804", - "pubmed_id": null, + "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", "title": null }, { - "PMCID": null, + "PMCID": "PMC2041839", "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17583532", "title": "Efficient calculation of exact mass isotopic distributions" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bit.10393", - "pubmed_id": null, + "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bit.10909", - "pubmed_id": null, + "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", "title": null }, { "PMCID": null, "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15922621", "title": "An automated method for the analysis of stable isotope labeling data in proteomics" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3", - "pubmed_id": null, + "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16458531", "title": "Efficient calculation of accurate masses of isotopic peaks" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac951158i", - "pubmed_id": null, + "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/0020-7381(83)85053-0", + "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", + "doi": "10.1016/0020-7381(83)85053-0", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "The Python Programming Languagehttp://www.python.org/", + "citation": "Rossum G.V. The Python Programming Language. [(accessed on 21 July 2013)]. Available online: http://www.python.org/", "doi": null, "pubmed_id": null, "title": null @@ -927,7 +927,7 @@ "PMCID": null, "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. Model. 1999;17:57\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10660911", "title": "Python: A programming language for software integration and development" }, { @@ -945,119 +945,21 @@ "title": "Design Patterns: Elements of Reusable Object-Oriented Software" }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N.B. Error analysis and propagation in metabolomics data analysis. Comp. Struct Biotech. J. 2013;4:e201301006.", - "doi": "https://doi.org/10.5936/csbj.201301006", - "pubmed_id": null, + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": "Error analysis and propagation in metabolomics data analysis" }, { "PMCID": null, - "citation": "Moseley Bioinformatics Laboratory Software Repository for downloadhttp://bioinformatics.cesb.uky.edu/bin/view/Main/SoftwareDevelopment/", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. 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Metabolic profiling technologies for biomarker discovery in biomedicine and drug development. Pharmacogenomics. 2006;7:1055\u20131075.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17054416", "title": null }, { "PMCID": null, "citation": "Oresic M, Vidal-Puig A, Hanninen V. Metabolomic approaches to phenotype characterization and applications to complex diseases. Expert Review of Molecular Diagnostics. 2006;6:575\u2013585.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16824031", "title": null }, { @@ -97,24 +97,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2724746", "citation": "Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457:910\u2013914.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19212411", "title": null }, { "PMCID": null, "citation": "Griffiths William J., T. K., Wang Yuqin, Kohl Matthias, Enot David P., Deigner H-P. Targeted Metabolomics for Biomarker Discovery. Angew. Chem. Int. Ed. 2010;49:5426\u20135446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20629054", "title": null }, { "PMCID": null, "citation": "Theodoridis G, Gika HG, Wilson ID. Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies. Mass Spectrom. Rev. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "21384411", "title": null }, { @@ -128,14 +128,14 @@ "PMCID": null, "citation": "Andrew Clayton T, Lindon JC, Cloarec O, Antti H, Charuel C, Hanton G, Provost J-P, Le Net J-L\u00d8, Baker D, Walley RJ, Everett JR, Nicholson JK. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature. 2006;440:1073\u20131077.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16625200", "title": null }, { "PMCID": null, "citation": "Harrigan GG, Brackett DJ, Boros LG. Medicinal chemistry, metabolic profiling and drug target discovery: A role for metabolic profiling in reverse pharmacology and chemical genetics. Mini-Reviews in Medicinal Chemistry. 2005;5:13\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15638788", "title": null }, { @@ -149,133 +149,133 @@ "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN. Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metab. Rev. 2006;38:707\u2013732.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17145697", "title": null }, { "PMCID": null, "citation": "Robertson DG. Metabonomics in toxicology: A review. Toxicological Sciences. 2005;85:809\u2013822.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15689416", "title": null }, { "PMCID": null, "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15544433", "title": null }, { - "PMCID": null, + "PMCID": "PMC2140249", "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17786640", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { "PMCID": null, "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19478804", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21466455", "title": null }, { - "PMCID": null, + "PMCID": "PMC3087304", "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21350847", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { "PMCID": null, "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16258367", "title": null }, { "PMCID": null, "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15611129", "title": null }, { - "PMCID": null, + "PMCID": "PMC2917841", "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20686576", "title": null }, { "PMCID": null, "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15663322", "title": null }, { @@ -286,122 +286,122 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM)) Molecular Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley HNB. Error Analysis and Propagation in Metabolomics Data Analysis. Comp Struct Biotech J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN, Jardetzky O. Combined use of proton NMR and gas chromatography-mass spectra for metabolite monitoring and in vivo proton NMR assignments. Biochimica et Biophysica Acta. 1986;882:154\u2013167.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3011112", "title": null }, { "PMCID": null, "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "11062433", "title": null }, { - "PMCID": null, + "PMCID": "PMC3746802", "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22608776", "title": null }, { - "PMCID": null, + "PMCID": "PMC3430598", "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study. BMC Genomics. 2012;13:334.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22823888", "title": null }, { - "PMCID": null, + "PMCID": "PMC3384197", "citation": "Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, Phang JM. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci U S A. 2012;109:8983\u20138988.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22615405", "title": null }, { - "PMCID": null, + "PMCID": "PMC3703516", "citation": "Dong C, Yuan T, Wu Y, Wang Y, Fan TW, Miriyala S, Lin Y, Yao J, Shi J, Kang T, Lorkiewicz P, St Clair D, Hung MC, Evers BM, Zhou BP. Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 2013;23:316\u2013331.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23453623", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2475696", "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18364355", "title": null }, { "PMCID": null, "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15994921", "title": null }, { "PMCID": null, "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9612242", "title": null }, { "PMCID": null, "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16317166", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { "PMCID": null, "citation": "Yang TH, Wittmann C, Heinzle E. Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum. Metab Eng. 2006;8:432\u2013446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16750927", "title": null }, { - "PMCID": null, + "PMCID": "PMC2952699", "citation": "Paul Lee W-N, P. N. W., Xuc Jun, Liang Go Vay. Tracer-based Metabolomics: Concepts and Practices. Clinical Biochemistry. 2010;43:1269\u20131277.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20713038", "title": null }, { @@ -419,38 +419,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TW, Lorkiewicz P, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol Ther. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Fan TWM, Colmer TD, Lane AN, Higashi RM. Determination of Metabolites by Proton Nmr and Gc Analysis for Organic Osmolytes in Crude Tissue Extracts. Analytical Biochemistry. 1993;214:260\u2013271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8250233", "title": null }, { "PMCID": null, "citation": "Gradwell MJ, Fan TWM, Lane AN. Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional 1H-31P NMR heteronuclear total correlation spectroscopy (hetero TOCSY) Analytical Biochemistry. 1998;263:139\u2013149.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9799525", "title": null }, { @@ -475,17 +475,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { - "PMCID": null, + "PMCID": "PMC3282107", "citation": "Yuneva MO, Fan TW-M, Higashi RM, Allen TA, Balakrishnan A, Goga A, Ferraris DV, Tsukamoto T, Wang C, Seo Y, Chen X, Bishop JM. The Metabolic Profile of Tumors Depends on Both the Responsible Genetic Lesion and Tissue Type Cell Metab. 2012;15:157\u2013170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22326218", "title": null }, { @@ -496,10 +496,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2847149", "citation": "Allwood JW, Erban A, de Koning S, Dunn WB, Luedemann A, Lommen A, Kay L, Loscher R, Kopka J, Goodacre R. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20376177", "title": null }, { @@ -513,144 +513,395 @@ "PMCID": null, "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16448047", "title": null }, { "PMCID": null, "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 2005;22:1155\u20131169.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16240456", "title": null }, { "PMCID": null, "citation": "Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, Goodacre R. Global Metabolic Profiling of Escherichia coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites. Anal. Chem. 2008;80:2939\u20132948.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18331064", "title": null }, { "PMCID": null, "citation": "Sellick CA, Hansen R, Maqsood AR, Dunn WB, Stephens GM, Goodacre R, Dickson AJ. Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells. Analytical Chemistry. 2009;81:174\u2013183.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19061395", "title": null }, { "PMCID": null, "citation": "Bolten CJ, Kiefer P, Letisse F, Portais JC, Wittmann C. Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17411014", "title": null }, { "PMCID": null, "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1514678", "title": null }, { "PMCID": null, "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12103361", "title": null }, { "PMCID": null, "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12009699", "title": null }, { "PMCID": null, "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17630720", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3501132", "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. Metabolomics. 2012 In press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23175637", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJ, Lorkiewicz PK, Higashi RM, Fan TW, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, + "pubmed_id": "22225880", + "title": null + }, + { + "PMCID": "PMC4486296", + "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", + "doi": null, + "pubmed_id": "26146495", + "title": null + }, + { + "PMCID": null, + "citation": "Fan TWM, Bandura LL, Higashi RM, Lane AN. 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Metabolomics. 2012;8:517\u2013527.", + "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", + "doi": null, + "pubmed_id": "17964943", + "title": null + }, + { + "PMCID": null, + "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", + "doi": null, + "pubmed_id": "8811175", + "title": null + }, + { + "PMCID": null, + "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", + "doi": null, + "pubmed_id": "10863556", + "title": null + }, + { + "PMCID": "PMC1794290", + "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A. 2007;104:1777\u20131782.", + "doi": null, + "pubmed_id": "17267599", + "title": null + } + ], + "results": null, + "title": "Stable isotope-labeled tracers for metabolic pathway elucidation by GC-MS and FT-MS." + }, + "https://doi.org/10.3390/metabo3040853": { + "PMCID": "PMC3882318", + "abstract": "New metabolomics applications of ultra-high resolution and accuracy mass spectrometry can provide thousands of detectable isotopologues, with the number of potentially detectable isotopologues increasing exponentially with the number of stable isotopes used in newer isotope tracing methods like stable isotope-resolved metabolomics (SIRM) experiments. This huge increase in usable data requires software capable of correcting the large number of isotopologue peaks resulting from SIRM experiments in a timely manner. We describe the design of a new algorithm and software system capable of handling these high volumes of data, while including quality control methods for maintaining data quality. We validate this new algorithm against a previous single isotope correction algorithm in a two-step cross-validation. Next, we demonstrate the algorithm and correct for the effects of natural abundance for both (13)C and (15)N isotopes on a set of raw isotopologue intensities of UDP-N-acetyl-D-glucosamine derived from a (13)C/(15)N-tracing experiment. Finally, we demonstrate the algorithm on a full omics-level dataset.", + "authors": [ + { + "ORCID": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", + "author_id": null, + "firstname": "William J", + "initials": "WJ", + "lastname": "Carreer" + }, + { + "ORCID": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", + "author_id": null, + "firstname": "Robert M", + "initials": "RM", + "lastname": "Flight" + }, + { + "ORCID": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", + "author_id": null, + "firstname": "Hunter N B", + "initials": "HN", + "lastname": "Moseley" + } + ], + "conclusions": null, + "copyrights": null, + "doi": "10.3390/metabo3040853", + "grants": [ + "P20 GM103436", + "P20 RR016481", + "R01 ES022191", + "U24 DK097215" + ], + "journal": "Metabolites", + "keywords": [ + "Fourier transform mass spectrometry", + "analytical derivation", + "multi-isotope natural abundance correction", + "parallelization", + "stable isotope tracing", + "stable isotope-resolved metabolomics" + ], + "methods": null, + "publication_date": { + "day": 10, + "month": 1, + "year": 2014 + }, + "pubmed_id": "24404440", + "queried_sources": [ + "PubMed" + ], + "references": [ + { + "PMCID": null, + "citation": "Rittenberg D., Schoenheimer R. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1937;121:235.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Fan TWM, Bandura LL, Higashi RM, Lane AN. Metabolomics-edited transcriptomics analysis of Se anticancer action in human lung cancer cells. Metabolomics. 2005;1:325\u2013339.", + "citation": "Schoenheimer R., Rittenberg D. The study of intermediary metabolism of animals with the aid of isotopes. Physiol. Rev. 1940;20:218.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Lane AN, Fan TW-M, Xie X, Moseley HN, Higashi RM. Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR Anal. Chim. Acta. 2009;651:201\u2013208.", + "citation": "Schoenheimer R., Rittenberg D. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1935;111:163.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Lorkiewicz P, Higashi RM, Lane AN, Fan TWM. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8:930\u2013939.", + "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", + "title": null + }, + { + "PMCID": "PMC2717907", + "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", + "title": null + }, + { + "PMCID": "PMC2757635", + "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", + "title": null + }, + { + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", + "title": null + }, + { + "PMCID": null, + "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", + "title": null + }, + { + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", + "title": null + }, + { + "PMCID": null, + "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", + "title": null + }, + { + "PMCID": null, + "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", + "title": null + }, + { + "PMCID": null, + "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", + "doi": null, + "pubmed_id": "10362629", + "title": null + }, + { + "PMCID": null, + "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", + "title": null + }, + { + "PMCID": "PMC2041839", + "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", + "doi": null, + "pubmed_id": "17583532", + "title": null + }, + { + "PMCID": null, + "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", + "title": null + }, + { + "PMCID": null, + "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", + "title": null + }, + { + "PMCID": null, + "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", + "doi": null, + "pubmed_id": "15922621", + "title": null + }, + { + "PMCID": null, + "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", + "title": null + }, + { + "PMCID": null, + "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", "doi": null, + "pubmed_id": "16458531", + "title": null + }, + { + "PMCID": null, + "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", + "title": null + }, + { + "PMCID": null, + "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", + "doi": "10.1016/0020-7381(83)85053-0", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", + "citation": "Rossum G.V. The Python Programming Language. [(accessed on 21 July 2013)]. Available online: http://www.python.org/", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", + "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. Model. 1999;17:57\u201361.", + "doi": null, + "pubmed_id": "10660911", + "title": null + }, + { + "PMCID": null, + "citation": "Oliphant T.E. A Guide to NumPy. Volume 1. Trelgol Publishing; Spanish Fork, UT, USA: 2006. pp. 1\u2013371.", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", + "citation": "Gamma E. Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional; Boston, MA, USA: 1995. pp. 1\u2013416.", "doi": null, "pubmed_id": null, "title": null }, + { + "PMCID": "PMC3647477", + "citation": "Moseley H.N.B. Error analysis and propagation in metabolomics data analysis. Comp. Struct Biotech. J. 2013;4:e201301006.", + "doi": null, + "pubmed_id": "23667718", + "title": null + }, { "PMCID": null, - "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A. 2007;104:1777\u20131782.", + "citation": "Moseley Bioinformatics Laboratory Software Repository for download. [(accessed on 21 July 2013)]. Available online: http://bioinformatics.cesb.uky.edu/bin/view/Main/SoftwareDevelopment/", "doi": null, "pubmed_id": null, "title": null } ], "results": null, - "title": "Stable isotope-labeled tracers for metabolic pathway elucidation by GC-MS and FT-MS." + "title": "A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets." } } \ No newline at end of file diff --git a/tests/testing_files/intermediate_results/ref_search/all/running_pubs2.json b/tests/testing_files/intermediate_results/ref_search/all/running_pubs2.json index 597c129..ebb1d78 100644 --- a/tests/testing_files/intermediate_results/ref_search/all/running_pubs2.json +++ b/tests/testing_files/intermediate_results/ref_search/all/running_pubs2.json @@ -46,7 +46,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "doi": "10.1007/978-1-4939-1258-2_11", "grants": [ "1R01CA118434-01A2", "5P20RR018733", @@ -79,14 +79,14 @@ "PMCID": null, "citation": "Schlotterbeck G, Ross A, Dieterle F, Senn H. Metabolic profiling technologies for biomarker discovery in biomedicine and drug development. Pharmacogenomics. 2006;7:1055\u20131075.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17054416", "title": null }, { "PMCID": null, "citation": "Oresic M, Vidal-Puig A, Hanninen V. Metabolomic approaches to phenotype characterization and applications to complex diseases. Expert Review of Molecular Diagnostics. 2006;6:575\u2013585.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16824031", "title": null }, { @@ -97,24 +97,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2724746", "citation": "Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457:910\u2013914.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19212411", "title": null }, { "PMCID": null, "citation": "Griffiths William J., T. K., Wang Yuqin, Kohl Matthias, Enot David P., Deigner H-P. Targeted Metabolomics for Biomarker Discovery. Angew. Chem. Int. Ed. 2010;49:5426\u20135446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20629054", "title": null }, { "PMCID": null, "citation": "Theodoridis G, Gika HG, Wilson ID. Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies. Mass Spectrom. Rev. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "21384411", "title": null }, { @@ -128,14 +128,14 @@ "PMCID": null, "citation": "Andrew Clayton T, Lindon JC, Cloarec O, Antti H, Charuel C, Hanton G, Provost J-P, Le Net J-L\u00d8, Baker D, Walley RJ, Everett JR, Nicholson JK. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature. 2006;440:1073\u20131077.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16625200", "title": null }, { "PMCID": null, "citation": "Harrigan GG, Brackett DJ, Boros LG. Medicinal chemistry, metabolic profiling and drug target discovery: A role for metabolic profiling in reverse pharmacology and chemical genetics. Mini-Reviews in Medicinal Chemistry. 2005;5:13\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15638788", "title": null }, { @@ -149,133 +149,133 @@ "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN. Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metab. Rev. 2006;38:707\u2013732.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17145697", "title": null }, { "PMCID": null, "citation": "Robertson DG. Metabonomics in toxicology: A review. Toxicological Sciences. 2005;85:809\u2013822.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15689416", "title": null }, { "PMCID": null, "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15544433", "title": null }, { - "PMCID": null, + "PMCID": "PMC2140249", "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17786640", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { "PMCID": null, "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19478804", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21466455", "title": null }, { - "PMCID": null, + "PMCID": "PMC3087304", "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21350847", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { "PMCID": null, "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16258367", "title": null }, { "PMCID": null, "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15611129", "title": null }, { - "PMCID": null, + "PMCID": "PMC2917841", "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20686576", "title": null }, { "PMCID": null, "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15663322", "title": null }, { @@ -286,122 +286,122 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM)) Molecular Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley HNB. Error Analysis and Propagation in Metabolomics Data Analysis. Comp Struct Biotech J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN, Jardetzky O. Combined use of proton NMR and gas chromatography-mass spectra for metabolite monitoring and in vivo proton NMR assignments. Biochimica et Biophysica Acta. 1986;882:154\u2013167.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3011112", "title": null }, { "PMCID": null, "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "11062433", "title": null }, { - "PMCID": null, + "PMCID": "PMC3746802", "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22608776", "title": null }, { - "PMCID": null, + "PMCID": "PMC3430598", "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study. BMC Genomics. 2012;13:334.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22823888", "title": null }, { - "PMCID": null, + "PMCID": "PMC3384197", "citation": "Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, Phang JM. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci U S A. 2012;109:8983\u20138988.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22615405", "title": null }, { - "PMCID": null, + "PMCID": "PMC3703516", "citation": "Dong C, Yuan T, Wu Y, Wang Y, Fan TW, Miriyala S, Lin Y, Yao J, Shi J, Kang T, Lorkiewicz P, St Clair D, Hung MC, Evers BM, Zhou BP. Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 2013;23:316\u2013331.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23453623", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2475696", "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18364355", "title": null }, { "PMCID": null, "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15994921", "title": null }, { "PMCID": null, "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9612242", "title": null }, { "PMCID": null, "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16317166", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { "PMCID": null, "citation": "Yang TH, Wittmann C, Heinzle E. Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum. Metab Eng. 2006;8:432\u2013446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16750927", "title": null }, { - "PMCID": null, + "PMCID": "PMC2952699", "citation": "Paul Lee W-N, P. N. W., Xuc Jun, Liang Go Vay. Tracer-based Metabolomics: Concepts and Practices. Clinical Biochemistry. 2010;43:1269\u20131277.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20713038", "title": null }, { @@ -419,38 +419,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TW, Lorkiewicz P, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol Ther. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Fan TWM, Colmer TD, Lane AN, Higashi RM. Determination of Metabolites by Proton Nmr and Gc Analysis for Organic Osmolytes in Crude Tissue Extracts. Analytical Biochemistry. 1993;214:260\u2013271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8250233", "title": null }, { "PMCID": null, "citation": "Gradwell MJ, Fan TWM, Lane AN. Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional 1H-31P NMR heteronuclear total correlation spectroscopy (hetero TOCSY) Analytical Biochemistry. 1998;263:139\u2013149.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9799525", "title": null }, { @@ -475,17 +475,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { - "PMCID": null, + "PMCID": "PMC3282107", "citation": "Yuneva MO, Fan TW-M, Higashi RM, Allen TA, Balakrishnan A, Goga A, Ferraris DV, Tsukamoto T, Wang C, Seo Y, Chen X, Bishop JM. The Metabolic Profile of Tumors Depends on Both the Responsible Genetic Lesion and Tissue Type Cell Metab. 2012;15:157\u2013170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22326218", "title": null }, { @@ -496,10 +496,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2847149", "citation": "Allwood JW, Erban A, de Koning S, Dunn WB, Luedemann A, Lommen A, Kay L, Loscher R, Kopka J, Goodacre R. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20376177", "title": null }, { @@ -513,91 +513,91 @@ "PMCID": null, "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16448047", "title": null }, { "PMCID": null, "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 2005;22:1155\u20131169.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16240456", "title": null }, { "PMCID": null, "citation": "Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, Goodacre R. Global Metabolic Profiling of Escherichia coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites. Anal. Chem. 2008;80:2939\u20132948.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18331064", "title": null }, { "PMCID": null, "citation": "Sellick CA, Hansen R, Maqsood AR, Dunn WB, Stephens GM, Goodacre R, Dickson AJ. Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells. Analytical Chemistry. 2009;81:174\u2013183.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19061395", "title": null }, { "PMCID": null, "citation": "Bolten CJ, Kiefer P, Letisse F, Portais JC, Wittmann C. Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17411014", "title": null }, { "PMCID": null, "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1514678", "title": null }, { "PMCID": null, "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12103361", "title": null }, { "PMCID": null, "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12009699", "title": null }, { "PMCID": null, "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17630720", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3501132", "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. Metabolomics. 2012 In press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23175637", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJ, Lorkiewicz PK, Higashi RM, Fan TW, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { @@ -608,45 +608,45 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane AN, Fan TW-M, Xie X, Moseley HN, Higashi RM. Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR Anal. Chim. Acta. 2009;651:201\u2013208.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz P, Higashi RM, Lane AN, Fan TWM. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8:930\u2013939.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8811175", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10863556", "title": null }, { - "PMCID": null, + "PMCID": "PMC1794290", "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A. 2007;104:1777\u20131782.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17267599", "title": null } ], @@ -698,8 +698,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 29, + "month": 9, "year": 2014 }, "pubmed_id": null, @@ -711,242 +711,255 @@ "title": "Development of large-scale metabolite identification methods for metabolomics" }, "https://doi.org/10.3390/metabo3040853": { - "PMCID": null, - "abstract": null, + "PMCID": "PMC3882318", + "abstract": "New metabolomics applications of ultra-high resolution and accuracy mass spectrometry can provide thousands of detectable isotopologues, with the number of potentially detectable isotopologues increasing exponentially with the number of stable isotopes used in newer isotope tracing methods like stable isotope-resolved metabolomics (SIRM) experiments. This huge increase in usable data requires software capable of correcting the large number of isotopologue peaks resulting from SIRM experiments in a timely manner. We describe the design of a new algorithm and software system capable of handling these high volumes of data, while including quality control methods for maintaining data quality. We validate this new algorithm against a previous single isotope correction algorithm in a two-step cross-validation. Next, we demonstrate the algorithm and correct for the effects of natural abundance for both (13)C and (15)N isotopes on a set of raw isotopologue intensities of UDP-N-acetyl-D-glucosamine derived from a (13)C/(15)N-tracing experiment. Finally, we demonstrate the algorithm on a full omics-level dataset.", "authors": [ { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "William", - "initials": null, + "firstname": "William J", + "initials": "WJ", "lastname": "Carreer" }, { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "Robert", - "initials": null, + "firstname": "Robert M", + "initials": "RM", "lastname": "Flight" }, { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "Hunter", - "initials": null, + "firstname": "Hunter N B", + "initials": "HN", "lastname": "Moseley" } ], "conclusions": null, "copyrights": null, "doi": "10.3390/metabo3040853", - "grants": [], - "journal": "MDPI AG", - "keywords": null, + "grants": [ + "P20 GM103436", + "P20 RR016481", + "R01 ES022191", + "U24 DK097215" + ], + "journal": "Metabolites", + "keywords": [ + "Fourier transform mass spectrometry", + "analytical derivation", + "multi-isotope natural abundance correction", + "parallelization", + "stable isotope tracing", + "stable isotope-resolved metabolomics" + ], "methods": null, "publication_date": { - "day": null, - "month": null, - "year": 2013 + "day": 10, + "month": 1, + "year": 2014 }, - "pubmed_id": null, + "pubmed_id": "24404440", "queried_sources": [ + "PubMed", "Crossref" ], "references": [ { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/S0021-9258(18)74342-1", + "citation": "Rittenberg D., Schoenheimer R. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1937;121:235.", + "doi": "10.1016/S0021-9258(18)74342-1", "pubmed_id": null, "title": "Deuterium as an indicator in the study of intermediary metabolism" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1152/physrev.1940.20.2.218", + "citation": "Schoenheimer R., Rittenberg D. The study of intermediary metabolism of animals with the aid of isotopes. Physiol. Rev. 1940;20:218.", + "doi": "10.1152/physrev.1940.20.2.218", "pubmed_id": null, "title": "The study of intermediary metabolism of animals with the aid of isotopes" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/S0021-9258(18)75075-8", + "citation": "Schoenheimer R., Rittenberg D. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1935;111:163.", + "doi": "10.1016/S0021-9258(18)75075-8", "pubmed_id": null, "title": "Deuterium as an indicator in the study of intermediary metabolism" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.2174/1568009033481769", - "pubmed_id": null, + "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1476-4598-8-41", - "pubmed_id": null, + "PMCID": "PMC2717907", + "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2009.08.032", - "pubmed_id": null, + "PMCID": "PMC2757635", + "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac061906b", - "pubmed_id": null, + "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/bp000058h", - "pubmed_id": null, + "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1046/j.1432-1033.2003.03448.x", - "pubmed_id": null, + "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", "title": null }, { "PMCID": null, - "citation": null, + "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10362629", "title": "Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bms.1200200804", - "pubmed_id": null, + "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", "title": null }, { - "PMCID": null, - "citation": null, + "PMCID": "PMC2041839", + "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17583532", "title": "Efficient calculation of exact mass isotopic distributions" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bit.10393", - "pubmed_id": null, + "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bit.10909", - "pubmed_id": null, + "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", "title": null }, { "PMCID": null, - "citation": null, + "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15922621", "title": "An automated method for the analysis of stable isotope labeling data in proteomics" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3", - "pubmed_id": null, + "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", "title": null }, { "PMCID": null, - "citation": null, + "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16458531", "title": "Efficient calculation of accurate masses of isotopic peaks" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac951158i", - "pubmed_id": null, + "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/0020-7381(83)85053-0", + "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", + "doi": "10.1016/0020-7381(83)85053-0", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "The Python Programming Languagehttp://www.python.org/", + "citation": "Rossum G.V. The Python Programming Language. [(accessed on 21 July 2013)]. Available online: http://www.python.org/", "doi": null, "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": null, + "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. Model. 1999;17:57\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10660911", "title": "Python: A programming language for software integration and development" }, { "PMCID": null, - "citation": null, + "citation": "Oliphant T.E. A Guide to NumPy. Volume 1. Trelgol Publishing; Spanish Fork, UT, USA: 2006. pp. 1\u2013371.", "doi": null, "pubmed_id": null, "title": "A Guide to NumPy" }, { "PMCID": null, - "citation": null, + "citation": "Gamma E. Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional; Boston, MA, USA: 1995. pp. 1\u2013416.", "doi": null, "pubmed_id": null, "title": "Design Patterns: Elements of Reusable Object-Oriented Software" }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", - "pubmed_id": null, + "PMCID": "PMC3647477", + "citation": "Moseley H.N.B. Error analysis and propagation in metabolomics data analysis. Comp. Struct Biotech. J. 2013;4:e201301006.", + "doi": "10.5936/csbj.201301006", + "pubmed_id": "23667718", "title": "Error analysis and propagation in metabolomics data analysis" }, { "PMCID": null, - "citation": "Moseley Bioinformatics Laboratory Software Repository for downloadhttp://bioinformatics.cesb.uky.edu/bin/view/Main/SoftwareDevelopment/", + "citation": "Moseley Bioinformatics Laboratory Software Repository for download. [(accessed on 21 July 2013)]. Available online: http://bioinformatics.cesb.uky.edu/bin/view/Main/SoftwareDevelopment/", "doi": null, "pubmed_id": null, "title": null } ], "results": null, - "title": "A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets" + "title": "A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets." } } \ No newline at end of file diff --git a/tests/testing_files/intermediate_results/ref_search/all/running_pubs3.json b/tests/testing_files/intermediate_results/ref_search/all/running_pubs3.json index 78f68b2..ebb1d78 100644 --- a/tests/testing_files/intermediate_results/ref_search/all/running_pubs3.json +++ b/tests/testing_files/intermediate_results/ref_search/all/running_pubs3.json @@ -46,7 +46,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "doi": "10.1007/978-1-4939-1258-2_11", "grants": [ "1R01CA118434-01A2", "5P20RR018733", @@ -79,14 +79,14 @@ "PMCID": null, "citation": "Schlotterbeck G, Ross A, Dieterle F, Senn H. Metabolic profiling technologies for biomarker discovery in biomedicine and drug development. Pharmacogenomics. 2006;7:1055\u20131075.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17054416", "title": null }, { "PMCID": null, "citation": "Oresic M, Vidal-Puig A, Hanninen V. Metabolomic approaches to phenotype characterization and applications to complex diseases. Expert Review of Molecular Diagnostics. 2006;6:575\u2013585.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16824031", "title": null }, { @@ -97,24 +97,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2724746", "citation": "Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457:910\u2013914.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19212411", "title": null }, { "PMCID": null, "citation": "Griffiths William J., T. K., Wang Yuqin, Kohl Matthias, Enot David P., Deigner H-P. Targeted Metabolomics for Biomarker Discovery. Angew. Chem. Int. Ed. 2010;49:5426\u20135446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20629054", "title": null }, { "PMCID": null, "citation": "Theodoridis G, Gika HG, Wilson ID. Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies. Mass Spectrom. Rev. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "21384411", "title": null }, { @@ -128,14 +128,14 @@ "PMCID": null, "citation": "Andrew Clayton T, Lindon JC, Cloarec O, Antti H, Charuel C, Hanton G, Provost J-P, Le Net J-L\u00d8, Baker D, Walley RJ, Everett JR, Nicholson JK. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature. 2006;440:1073\u20131077.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16625200", "title": null }, { "PMCID": null, "citation": "Harrigan GG, Brackett DJ, Boros LG. Medicinal chemistry, metabolic profiling and drug target discovery: A role for metabolic profiling in reverse pharmacology and chemical genetics. Mini-Reviews in Medicinal Chemistry. 2005;5:13\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15638788", "title": null }, { @@ -149,133 +149,133 @@ "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN. Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metab. Rev. 2006;38:707\u2013732.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17145697", "title": null }, { "PMCID": null, "citation": "Robertson DG. Metabonomics in toxicology: A review. Toxicological Sciences. 2005;85:809\u2013822.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15689416", "title": null }, { "PMCID": null, "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15544433", "title": null }, { - "PMCID": null, + "PMCID": "PMC2140249", "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17786640", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { "PMCID": null, "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19478804", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21466455", "title": null }, { - "PMCID": null, + "PMCID": "PMC3087304", "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21350847", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { "PMCID": null, "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16258367", "title": null }, { "PMCID": null, "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15611129", "title": null }, { - "PMCID": null, + "PMCID": "PMC2917841", "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20686576", "title": null }, { "PMCID": null, "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15663322", "title": null }, { @@ -286,122 +286,122 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM)) Molecular Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley HNB. Error Analysis and Propagation in Metabolomics Data Analysis. Comp Struct Biotech J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN, Jardetzky O. Combined use of proton NMR and gas chromatography-mass spectra for metabolite monitoring and in vivo proton NMR assignments. Biochimica et Biophysica Acta. 1986;882:154\u2013167.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3011112", "title": null }, { "PMCID": null, "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "11062433", "title": null }, { - "PMCID": null, + "PMCID": "PMC3746802", "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22608776", "title": null }, { - "PMCID": null, + "PMCID": "PMC3430598", "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study. BMC Genomics. 2012;13:334.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22823888", "title": null }, { - "PMCID": null, + "PMCID": "PMC3384197", "citation": "Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, Phang JM. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci U S A. 2012;109:8983\u20138988.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22615405", "title": null }, { - "PMCID": null, + "PMCID": "PMC3703516", "citation": "Dong C, Yuan T, Wu Y, Wang Y, Fan TW, Miriyala S, Lin Y, Yao J, Shi J, Kang T, Lorkiewicz P, St Clair D, Hung MC, Evers BM, Zhou BP. Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 2013;23:316\u2013331.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23453623", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2475696", "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18364355", "title": null }, { "PMCID": null, "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15994921", "title": null }, { "PMCID": null, "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9612242", "title": null }, { "PMCID": null, "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16317166", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { "PMCID": null, "citation": "Yang TH, Wittmann C, Heinzle E. Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum. Metab Eng. 2006;8:432\u2013446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16750927", "title": null }, { - "PMCID": null, + "PMCID": "PMC2952699", "citation": "Paul Lee W-N, P. N. W., Xuc Jun, Liang Go Vay. Tracer-based Metabolomics: Concepts and Practices. Clinical Biochemistry. 2010;43:1269\u20131277.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20713038", "title": null }, { @@ -419,38 +419,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TW, Lorkiewicz P, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol Ther. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Fan TWM, Colmer TD, Lane AN, Higashi RM. Determination of Metabolites by Proton Nmr and Gc Analysis for Organic Osmolytes in Crude Tissue Extracts. Analytical Biochemistry. 1993;214:260\u2013271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8250233", "title": null }, { "PMCID": null, "citation": "Gradwell MJ, Fan TWM, Lane AN. Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional 1H-31P NMR heteronuclear total correlation spectroscopy (hetero TOCSY) Analytical Biochemistry. 1998;263:139\u2013149.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9799525", "title": null }, { @@ -475,17 +475,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { - "PMCID": null, + "PMCID": "PMC3282107", "citation": "Yuneva MO, Fan TW-M, Higashi RM, Allen TA, Balakrishnan A, Goga A, Ferraris DV, Tsukamoto T, Wang C, Seo Y, Chen X, Bishop JM. The Metabolic Profile of Tumors Depends on Both the Responsible Genetic Lesion and Tissue Type Cell Metab. 2012;15:157\u2013170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22326218", "title": null }, { @@ -496,10 +496,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2847149", "citation": "Allwood JW, Erban A, de Koning S, Dunn WB, Luedemann A, Lommen A, Kay L, Loscher R, Kopka J, Goodacre R. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20376177", "title": null }, { @@ -513,91 +513,91 @@ "PMCID": null, "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16448047", "title": null }, { "PMCID": null, "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 2005;22:1155\u20131169.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16240456", "title": null }, { "PMCID": null, "citation": "Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, Goodacre R. Global Metabolic Profiling of Escherichia coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites. Anal. Chem. 2008;80:2939\u20132948.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18331064", "title": null }, { "PMCID": null, "citation": "Sellick CA, Hansen R, Maqsood AR, Dunn WB, Stephens GM, Goodacre R, Dickson AJ. Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells. Analytical Chemistry. 2009;81:174\u2013183.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19061395", "title": null }, { "PMCID": null, "citation": "Bolten CJ, Kiefer P, Letisse F, Portais JC, Wittmann C. Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17411014", "title": null }, { "PMCID": null, "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1514678", "title": null }, { "PMCID": null, "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12103361", "title": null }, { "PMCID": null, "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12009699", "title": null }, { "PMCID": null, "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17630720", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3501132", "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. Metabolomics. 2012 In press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23175637", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJ, Lorkiewicz PK, Higashi RM, Fan TW, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { @@ -608,45 +608,45 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane AN, Fan TW-M, Xie X, Moseley HN, Higashi RM. Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR Anal. Chim. Acta. 2009;651:201\u2013208.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz P, Higashi RM, Lane AN, Fan TWM. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8:930\u2013939.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8811175", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10863556", "title": null }, { - "PMCID": null, + "PMCID": "PMC1794290", "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A. 2007;104:1777\u20131782.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17267599", "title": null } ], @@ -698,8 +698,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 29, + "month": 9, "year": 2014 }, "pubmed_id": null, @@ -716,26 +716,26 @@ "authors": [ { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "William", - "initials": null, + "firstname": "William J", + "initials": "WJ", "lastname": "Carreer" }, { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "Robert", - "initials": null, + "firstname": "Robert M", + "initials": "RM", "lastname": "Flight" }, { "ORCID": null, - "affiliation": null, + "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA; jim.carreer@uky.edu (W.J.C.); robert.flight@uky.edu (R.M.F.).", "author_id": null, - "firstname": "Hunter", - "initials": null, + "firstname": "Hunter N B", + "initials": "HN", "lastname": "Moseley" } ], @@ -748,7 +748,7 @@ "R01 ES022191", "U24 DK097215" ], - "journal": "MDPI AG", + "journal": "Metabolites", "keywords": [ "Fourier transform mass spectrometry", "analytical derivation", @@ -761,164 +761,164 @@ "publication_date": { "day": 10, "month": 1, - "year": 2013 + "year": 2014 }, "pubmed_id": "24404440", "queried_sources": [ - "Crossref", - "PubMed" + "PubMed", + "Crossref" ], "references": [ { "PMCID": null, "citation": "Rittenberg D., Schoenheimer R. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1937;121:235.", - "doi": "https://doi.org/10.1016/S0021-9258(18)74342-1", + "doi": "10.1016/S0021-9258(18)74342-1", "pubmed_id": null, "title": "Deuterium as an indicator in the study of intermediary metabolism" }, { "PMCID": null, "citation": "Schoenheimer R., Rittenberg D. The study of intermediary metabolism of animals with the aid of isotopes. Physiol. Rev. 1940;20:218.", - "doi": "https://doi.org/10.1152/physrev.1940.20.2.218", + "doi": "10.1152/physrev.1940.20.2.218", "pubmed_id": null, "title": "The study of intermediary metabolism of animals with the aid of isotopes" }, { "PMCID": null, "citation": "Schoenheimer R., Rittenberg D. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1935;111:163.", - "doi": "https://doi.org/10.1016/S0021-9258(18)75075-8", + "doi": "10.1016/S0021-9258(18)75075-8", "pubmed_id": null, "title": "Deuterium as an indicator in the study of intermediary metabolism" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.2174/1568009033481769", - "pubmed_id": null, + "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1476-4598-8-41", - "pubmed_id": null, + "PMCID": "PMC2717907", + "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2009.08.032", - "pubmed_id": null, + "PMCID": "PMC2757635", + "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac061906b", - "pubmed_id": null, + "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/bp000058h", - "pubmed_id": null, + "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1046/j.1432-1033.2003.03448.x", - "pubmed_id": null, + "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", "title": null }, { "PMCID": null, "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10362629", "title": "Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bms.1200200804", - "pubmed_id": null, + "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", "title": null }, { - "PMCID": null, + "PMCID": "PMC2041839", "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17583532", "title": "Efficient calculation of exact mass isotopic distributions" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bit.10393", - "pubmed_id": null, + "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bit.10909", - "pubmed_id": null, + "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", "title": null }, { "PMCID": null, "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15922621", "title": "An automated method for the analysis of stable isotope labeling data in proteomics" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3", - "pubmed_id": null, + "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16458531", "title": "Efficient calculation of accurate masses of isotopic peaks" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac951158i", - "pubmed_id": null, + "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/0020-7381(83)85053-0", + "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", + "doi": "10.1016/0020-7381(83)85053-0", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "The Python Programming Languagehttp://www.python.org/", + "citation": "Rossum G.V. The Python Programming Language. [(accessed on 21 July 2013)]. Available online: http://www.python.org/", "doi": null, "pubmed_id": null, "title": null @@ -927,7 +927,7 @@ "PMCID": null, "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. 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Toxicological Sciences. 2005;85:809\u2013822.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15689416", "title": null }, { "PMCID": null, "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15544433", "title": null }, { - "PMCID": null, + "PMCID": "PMC2140249", "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17786640", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { "PMCID": null, "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19478804", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21466455", "title": null }, { - "PMCID": null, + "PMCID": "PMC3087304", "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21350847", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { "PMCID": null, "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16258367", "title": null }, { "PMCID": null, "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15611129", "title": null }, { - "PMCID": null, + "PMCID": "PMC2917841", "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20686576", "title": null }, { "PMCID": null, "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15663322", "title": null }, { @@ -286,122 +286,122 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM)) Molecular Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley HNB. Error Analysis and Propagation in Metabolomics Data Analysis. Comp Struct Biotech J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN, Jardetzky O. Combined use of proton NMR and gas chromatography-mass spectra for metabolite monitoring and in vivo proton NMR assignments. Biochimica et Biophysica Acta. 1986;882:154\u2013167.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3011112", "title": null }, { "PMCID": null, "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "11062433", "title": null }, { - "PMCID": null, + "PMCID": "PMC3746802", "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22608776", "title": null }, { - "PMCID": null, + "PMCID": "PMC3430598", "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study. BMC Genomics. 2012;13:334.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22823888", "title": null }, { - "PMCID": null, + "PMCID": "PMC3384197", "citation": "Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, Phang JM. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci U S A. 2012;109:8983\u20138988.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22615405", "title": null }, { - "PMCID": null, + "PMCID": "PMC3703516", "citation": "Dong C, Yuan T, Wu Y, Wang Y, Fan TW, Miriyala S, Lin Y, Yao J, Shi J, Kang T, Lorkiewicz P, St Clair D, Hung MC, Evers BM, Zhou BP. Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 2013;23:316\u2013331.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23453623", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2475696", "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18364355", "title": null }, { "PMCID": null, "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15994921", "title": null }, { "PMCID": null, "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9612242", "title": null }, { "PMCID": null, "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16317166", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { "PMCID": null, "citation": "Yang TH, Wittmann C, Heinzle E. Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum. Metab Eng. 2006;8:432\u2013446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16750927", "title": null }, { - "PMCID": null, + "PMCID": "PMC2952699", "citation": "Paul Lee W-N, P. N. W., Xuc Jun, Liang Go Vay. Tracer-based Metabolomics: Concepts and Practices. Clinical Biochemistry. 2010;43:1269\u20131277.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20713038", "title": null }, { @@ -419,38 +419,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TW, Lorkiewicz P, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol Ther. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Fan TWM, Colmer TD, Lane AN, Higashi RM. Determination of Metabolites by Proton Nmr and Gc Analysis for Organic Osmolytes in Crude Tissue Extracts. Analytical Biochemistry. 1993;214:260\u2013271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8250233", "title": null }, { "PMCID": null, "citation": "Gradwell MJ, Fan TWM, Lane AN. Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional 1H-31P NMR heteronuclear total correlation spectroscopy (hetero TOCSY) Analytical Biochemistry. 1998;263:139\u2013149.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9799525", "title": null }, { @@ -475,17 +475,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { - "PMCID": null, + "PMCID": "PMC3282107", "citation": "Yuneva MO, Fan TW-M, Higashi RM, Allen TA, Balakrishnan A, Goga A, Ferraris DV, Tsukamoto T, Wang C, Seo Y, Chen X, Bishop JM. The Metabolic Profile of Tumors Depends on Both the Responsible Genetic Lesion and Tissue Type Cell Metab. 2012;15:157\u2013170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22326218", "title": null }, { @@ -496,10 +496,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2847149", "citation": "Allwood JW, Erban A, de Koning S, Dunn WB, Luedemann A, Lommen A, Kay L, Loscher R, Kopka J, Goodacre R. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20376177", "title": null }, { @@ -513,91 +513,91 @@ "PMCID": null, "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16448047", "title": null }, { "PMCID": null, "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 2005;22:1155\u20131169.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16240456", "title": null }, { "PMCID": null, "citation": "Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, Goodacre R. Global Metabolic Profiling of Escherichia coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites. Anal. Chem. 2008;80:2939\u20132948.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18331064", "title": null }, { "PMCID": null, "citation": "Sellick CA, Hansen R, Maqsood AR, Dunn WB, Stephens GM, Goodacre R, Dickson AJ. Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells. Analytical Chemistry. 2009;81:174\u2013183.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19061395", "title": null }, { "PMCID": null, "citation": "Bolten CJ, Kiefer P, Letisse F, Portais JC, Wittmann C. Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17411014", "title": null }, { "PMCID": null, "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1514678", "title": null }, { "PMCID": null, "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12103361", "title": null }, { "PMCID": null, "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12009699", "title": null }, { "PMCID": null, "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17630720", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3501132", "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. Metabolomics. 2012 In press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23175637", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJ, Lorkiewicz PK, Higashi RM, Fan TW, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { @@ -608,45 +608,45 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane AN, Fan TW-M, Xie X, Moseley HN, Higashi RM. Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR Anal. Chim. Acta. 2009;651:201\u2013208.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz P, Higashi RM, Lane AN, Fan TWM. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8:930\u2013939.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8811175", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10863556", "title": null }, { - "PMCID": null, + "PMCID": "PMC1794290", "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. 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Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1937;121:235.", - "doi": "https://doi.org/10.1016/S0021-9258(18)74342-1", + "doi": "10.1016/S0021-9258(18)74342-1", "pubmed_id": null, "title": "Deuterium as an indicator in the study of intermediary metabolism" }, { "PMCID": null, "citation": "Schoenheimer R., Rittenberg D. The study of intermediary metabolism of animals with the aid of isotopes. Physiol. Rev. 1940;20:218.", - "doi": "https://doi.org/10.1152/physrev.1940.20.2.218", + "doi": "10.1152/physrev.1940.20.2.218", "pubmed_id": null, "title": "The study of intermediary metabolism of animals with the aid of isotopes" }, { "PMCID": null, "citation": "Schoenheimer R., Rittenberg D. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1935;111:163.", - "doi": "https://doi.org/10.1016/S0021-9258(18)75075-8", + "doi": "10.1016/S0021-9258(18)75075-8", "pubmed_id": null, "title": "Deuterium as an indicator in the study of intermediary metabolism" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.2174/1568009033481769", - "pubmed_id": null, + "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1476-4598-8-41", - "pubmed_id": null, + "PMCID": "PMC2717907", + "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2009.08.032", - "pubmed_id": null, + "PMCID": "PMC2757635", + "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-11-139", - "pubmed_id": null, + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac061906b", - "pubmed_id": null, + "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", "title": null }, { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", - "pubmed_id": null, + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/bp000058h", - "pubmed_id": null, + "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1046/j.1432-1033.2003.03448.x", - "pubmed_id": null, + "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", "title": null }, { "PMCID": null, "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10362629", "title": "Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bms.1200200804", - "pubmed_id": null, + "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", "title": null }, { - "PMCID": null, + "PMCID": "PMC2041839", "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17583532", "title": "Efficient calculation of exact mass isotopic distributions" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bit.10393", - "pubmed_id": null, + "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/bit.10909", - "pubmed_id": null, + "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", "title": null }, { "PMCID": null, "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15922621", "title": "An automated method for the analysis of stable isotope labeling data in proteomics" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3", - "pubmed_id": null, + "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16458531", "title": "Efficient calculation of accurate masses of isotopic peaks" }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1021/ac951158i", - "pubmed_id": null, + "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", "title": null }, { "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/0020-7381(83)85053-0", + "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", + "doi": "10.1016/0020-7381(83)85053-0", "pubmed_id": null, "title": null }, { "PMCID": null, - "citation": "The Python Programming Languagehttp://www.python.org/", + "citation": "Rossum G.V. The Python Programming Language. [(accessed on 21 July 2013)]. Available online: http://www.python.org/", "doi": null, "pubmed_id": null, "title": null @@ -927,7 +927,7 @@ "PMCID": null, "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. 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Toxicological Sciences. 2005;85:809\u2013822.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15689416", "title": null }, { "PMCID": null, "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15544433", "title": null }, { - "PMCID": null, + "PMCID": "PMC2140249", "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17786640", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { "PMCID": null, "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19478804", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21466455", "title": null }, { - "PMCID": null, + "PMCID": "PMC3087304", "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21350847", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { "PMCID": null, "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16258367", "title": null }, { "PMCID": null, "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15611129", "title": null }, { - "PMCID": null, + "PMCID": "PMC2917841", "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20686576", "title": null }, { "PMCID": null, "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15663322", "title": null }, { @@ -286,122 +286,122 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM)) Molecular Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley HNB. Error Analysis and Propagation in Metabolomics Data Analysis. Comp Struct Biotech J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN, Jardetzky O. Combined use of proton NMR and gas chromatography-mass spectra for metabolite monitoring and in vivo proton NMR assignments. Biochimica et Biophysica Acta. 1986;882:154\u2013167.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3011112", "title": null }, { "PMCID": null, "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "11062433", "title": null }, { - "PMCID": null, + "PMCID": "PMC3746802", "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22608776", "title": null }, { - "PMCID": null, + "PMCID": "PMC3430598", "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study. BMC Genomics. 2012;13:334.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22823888", "title": null }, { - "PMCID": null, + "PMCID": "PMC3384197", "citation": "Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, Phang JM. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci U S A. 2012;109:8983\u20138988.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22615405", "title": null }, { - "PMCID": null, + "PMCID": "PMC3703516", "citation": "Dong C, Yuan T, Wu Y, Wang Y, Fan TW, Miriyala S, Lin Y, Yao J, Shi J, Kang T, Lorkiewicz P, St Clair D, Hung MC, Evers BM, Zhou BP. Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 2013;23:316\u2013331.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23453623", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2475696", "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18364355", "title": null }, { "PMCID": null, "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15994921", "title": null }, { "PMCID": null, "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9612242", "title": null }, { "PMCID": null, "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16317166", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { "PMCID": null, "citation": "Yang TH, Wittmann C, Heinzle E. Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum. Metab Eng. 2006;8:432\u2013446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16750927", "title": null }, { - "PMCID": null, + "PMCID": "PMC2952699", "citation": "Paul Lee W-N, P. N. W., Xuc Jun, Liang Go Vay. Tracer-based Metabolomics: Concepts and Practices. Clinical Biochemistry. 2010;43:1269\u20131277.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20713038", "title": null }, { @@ -419,38 +419,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TW, Lorkiewicz P, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol Ther. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Fan TWM, Colmer TD, Lane AN, Higashi RM. Determination of Metabolites by Proton Nmr and Gc Analysis for Organic Osmolytes in Crude Tissue Extracts. Analytical Biochemistry. 1993;214:260\u2013271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8250233", "title": null }, { "PMCID": null, "citation": "Gradwell MJ, Fan TWM, Lane AN. Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional 1H-31P NMR heteronuclear total correlation spectroscopy (hetero TOCSY) Analytical Biochemistry. 1998;263:139\u2013149.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9799525", "title": null }, { @@ -475,17 +475,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { - "PMCID": null, + "PMCID": "PMC3282107", "citation": "Yuneva MO, Fan TW-M, Higashi RM, Allen TA, Balakrishnan A, Goga A, Ferraris DV, Tsukamoto T, Wang C, Seo Y, Chen X, Bishop JM. The Metabolic Profile of Tumors Depends on Both the Responsible Genetic Lesion and Tissue Type Cell Metab. 2012;15:157\u2013170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22326218", "title": null }, { @@ -496,10 +496,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2847149", "citation": "Allwood JW, Erban A, de Koning S, Dunn WB, Luedemann A, Lommen A, Kay L, Loscher R, Kopka J, Goodacre R. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20376177", "title": null }, { @@ -513,91 +513,91 @@ "PMCID": null, "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16448047", "title": null }, { "PMCID": null, "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 2005;22:1155\u20131169.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16240456", "title": null }, { "PMCID": null, "citation": "Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, Goodacre R. Global Metabolic Profiling of Escherichia coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites. Anal. Chem. 2008;80:2939\u20132948.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18331064", "title": null }, { "PMCID": null, "citation": "Sellick CA, Hansen R, Maqsood AR, Dunn WB, Stephens GM, Goodacre R, Dickson AJ. Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells. Analytical Chemistry. 2009;81:174\u2013183.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19061395", "title": null }, { "PMCID": null, "citation": "Bolten CJ, Kiefer P, Letisse F, Portais JC, Wittmann C. Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17411014", "title": null }, { "PMCID": null, "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1514678", "title": null }, { "PMCID": null, "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12103361", "title": null }, { "PMCID": null, "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12009699", "title": null }, { "PMCID": null, "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17630720", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3501132", "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. Metabolomics. 2012 In press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23175637", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJ, Lorkiewicz PK, Higashi RM, Fan TW, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { @@ -608,45 +608,45 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane AN, Fan TW-M, Xie X, Moseley HN, Higashi RM. Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR Anal. Chim. Acta. 2009;651:201\u2013208.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz P, Higashi RM, Lane AN, Fan TWM. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8:930\u2013939.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8811175", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10863556", "title": null }, { - "PMCID": null, + "PMCID": "PMC1794290", "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A. 2007;104:1777\u20131782.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17267599", "title": null } ], @@ -684,7 +684,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "doi": "10.3390/metabo3040853", "grants": [ "P20 GM103436", "P20 RR016481", @@ -735,126 +735,126 @@ { "PMCID": null, "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", - "doi": null, - "pubmed_id": null, + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", "title": null }, { "PMCID": null, "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", "title": null }, { "PMCID": null, "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10362629", "title": null }, { "PMCID": null, "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", "title": null }, { - "PMCID": null, + "PMCID": "PMC2041839", "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17583532", "title": null }, { "PMCID": null, "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", "title": null }, { "PMCID": null, "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", "title": null }, { "PMCID": null, "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15922621", "title": null }, { "PMCID": null, "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16458531", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", "title": null }, { "PMCID": null, "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", - "doi": null, + "doi": "10.1016/0020-7381(83)85053-0", "pubmed_id": null, "title": null }, @@ -869,7 +869,7 @@ "PMCID": null, "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. Model. 1999;17:57\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10660911", "title": null }, { @@ -887,10 +887,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N.B. Error analysis and propagation in metabolomics data analysis. Comp. Struct Biotech. J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { diff --git a/tests/testing_files/intermediate_results/ref_search/no_Crossref/running_pubs1.json b/tests/testing_files/intermediate_results/ref_search/no_Crossref/running_pubs1.json index c8d02f2..c79bd61 100644 --- a/tests/testing_files/intermediate_results/ref_search/no_Crossref/running_pubs1.json +++ b/tests/testing_files/intermediate_results/ref_search/no_Crossref/running_pubs1.json @@ -46,7 +46,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "doi": "10.1007/978-1-4939-1258-2_11", "grants": [ "1R01CA118434-01A2", "5P20RR018733", @@ -79,14 +79,14 @@ "PMCID": null, "citation": "Schlotterbeck G, Ross A, Dieterle F, Senn H. Metabolic profiling technologies for biomarker discovery in biomedicine and drug development. Pharmacogenomics. 2006;7:1055\u20131075.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17054416", "title": null }, { "PMCID": null, "citation": "Oresic M, Vidal-Puig A, Hanninen V. Metabolomic approaches to phenotype characterization and applications to complex diseases. Expert Review of Molecular Diagnostics. 2006;6:575\u2013585.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16824031", "title": null }, { @@ -97,24 +97,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2724746", "citation": "Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457:910\u2013914.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19212411", "title": null }, { "PMCID": null, "citation": "Griffiths William J., T. K., Wang Yuqin, Kohl Matthias, Enot David P., Deigner H-P. Targeted Metabolomics for Biomarker Discovery. Angew. Chem. Int. Ed. 2010;49:5426\u20135446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20629054", "title": null }, { "PMCID": null, "citation": "Theodoridis G, Gika HG, Wilson ID. Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies. Mass Spectrom. Rev. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "21384411", "title": null }, { @@ -128,14 +128,14 @@ "PMCID": null, "citation": "Andrew Clayton T, Lindon JC, Cloarec O, Antti H, Charuel C, Hanton G, Provost J-P, Le Net J-L\u00d8, Baker D, Walley RJ, Everett JR, Nicholson JK. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature. 2006;440:1073\u20131077.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16625200", "title": null }, { "PMCID": null, "citation": "Harrigan GG, Brackett DJ, Boros LG. Medicinal chemistry, metabolic profiling and drug target discovery: A role for metabolic profiling in reverse pharmacology and chemical genetics. Mini-Reviews in Medicinal Chemistry. 2005;5:13\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15638788", "title": null }, { @@ -149,133 +149,133 @@ "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN. Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metab. Rev. 2006;38:707\u2013732.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17145697", "title": null }, { "PMCID": null, "citation": "Robertson DG. Metabonomics in toxicology: A review. Toxicological Sciences. 2005;85:809\u2013822.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15689416", "title": null }, { "PMCID": null, "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15544433", "title": null }, { - "PMCID": null, + "PMCID": "PMC2140249", "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17786640", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { "PMCID": null, "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19478804", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21466455", "title": null }, { - "PMCID": null, + "PMCID": "PMC3087304", "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21350847", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { "PMCID": null, "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16258367", "title": null }, { "PMCID": null, "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15611129", "title": null }, { - "PMCID": null, + "PMCID": "PMC2917841", "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20686576", "title": null }, { "PMCID": null, "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15663322", "title": null }, { @@ -286,122 +286,122 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM)) Molecular Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley HNB. Error Analysis and Propagation in Metabolomics Data Analysis. Comp Struct Biotech J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN, Jardetzky O. Combined use of proton NMR and gas chromatography-mass spectra for metabolite monitoring and in vivo proton NMR assignments. Biochimica et Biophysica Acta. 1986;882:154\u2013167.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3011112", "title": null }, { "PMCID": null, "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "11062433", "title": null }, { - "PMCID": null, + "PMCID": "PMC3746802", "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22608776", "title": null }, { - "PMCID": null, + "PMCID": "PMC3430598", "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study. BMC Genomics. 2012;13:334.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22823888", "title": null }, { - "PMCID": null, + "PMCID": "PMC3384197", "citation": "Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, Phang JM. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci U S A. 2012;109:8983\u20138988.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22615405", "title": null }, { - "PMCID": null, + "PMCID": "PMC3703516", "citation": "Dong C, Yuan T, Wu Y, Wang Y, Fan TW, Miriyala S, Lin Y, Yao J, Shi J, Kang T, Lorkiewicz P, St Clair D, Hung MC, Evers BM, Zhou BP. Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 2013;23:316\u2013331.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23453623", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2475696", "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18364355", "title": null }, { "PMCID": null, "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15994921", "title": null }, { "PMCID": null, "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9612242", "title": null }, { "PMCID": null, "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16317166", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { "PMCID": null, "citation": "Yang TH, Wittmann C, Heinzle E. Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum. Metab Eng. 2006;8:432\u2013446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16750927", "title": null }, { - "PMCID": null, + "PMCID": "PMC2952699", "citation": "Paul Lee W-N, P. N. W., Xuc Jun, Liang Go Vay. Tracer-based Metabolomics: Concepts and Practices. Clinical Biochemistry. 2010;43:1269\u20131277.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20713038", "title": null }, { @@ -419,38 +419,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TW, Lorkiewicz P, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol Ther. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Fan TWM, Colmer TD, Lane AN, Higashi RM. Determination of Metabolites by Proton Nmr and Gc Analysis for Organic Osmolytes in Crude Tissue Extracts. Analytical Biochemistry. 1993;214:260\u2013271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8250233", "title": null }, { "PMCID": null, "citation": "Gradwell MJ, Fan TWM, Lane AN. Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional 1H-31P NMR heteronuclear total correlation spectroscopy (hetero TOCSY) Analytical Biochemistry. 1998;263:139\u2013149.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9799525", "title": null }, { @@ -475,17 +475,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { - "PMCID": null, + "PMCID": "PMC3282107", "citation": "Yuneva MO, Fan TW-M, Higashi RM, Allen TA, Balakrishnan A, Goga A, Ferraris DV, Tsukamoto T, Wang C, Seo Y, Chen X, Bishop JM. The Metabolic Profile of Tumors Depends on Both the Responsible Genetic Lesion and Tissue Type Cell Metab. 2012;15:157\u2013170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22326218", "title": null }, { @@ -496,10 +496,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2847149", "citation": "Allwood JW, Erban A, de Koning S, Dunn WB, Luedemann A, Lommen A, Kay L, Loscher R, Kopka J, Goodacre R. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20376177", "title": null }, { @@ -513,91 +513,91 @@ "PMCID": null, "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16448047", "title": null }, { "PMCID": null, "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 2005;22:1155\u20131169.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16240456", "title": null }, { "PMCID": null, "citation": "Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, Goodacre R. Global Metabolic Profiling of Escherichia coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites. Anal. Chem. 2008;80:2939\u20132948.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18331064", "title": null }, { "PMCID": null, "citation": "Sellick CA, Hansen R, Maqsood AR, Dunn WB, Stephens GM, Goodacre R, Dickson AJ. Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells. Analytical Chemistry. 2009;81:174\u2013183.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19061395", "title": null }, { "PMCID": null, "citation": "Bolten CJ, Kiefer P, Letisse F, Portais JC, Wittmann C. Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17411014", "title": null }, { "PMCID": null, "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1514678", "title": null }, { "PMCID": null, "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12103361", "title": null }, { "PMCID": null, "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12009699", "title": null }, { "PMCID": null, "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17630720", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3501132", "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. Metabolomics. 2012 In press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23175637", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJ, Lorkiewicz PK, Higashi RM, Fan TW, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { @@ -608,45 +608,45 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane AN, Fan TW-M, Xie X, Moseley HN, Higashi RM. Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR Anal. Chim. Acta. 2009;651:201\u2013208.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz P, Higashi RM, Lane AN, Fan TWM. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8:930\u2013939.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8811175", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10863556", "title": null }, { - "PMCID": null, + "PMCID": "PMC1794290", "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A. 2007;104:1777\u20131782.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17267599", "title": null } ], @@ -684,7 +684,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "doi": "10.3390/metabo3040853", "grants": [ "P20 GM103436", "P20 RR016481", @@ -735,126 +735,126 @@ { "PMCID": null, "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", - "doi": null, - "pubmed_id": null, + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", "title": null }, { "PMCID": null, "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", "title": null }, { "PMCID": null, "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10362629", "title": null }, { "PMCID": null, "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", "title": null }, { - "PMCID": null, + "PMCID": "PMC2041839", "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17583532", "title": null }, { "PMCID": null, "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", "title": null }, { "PMCID": null, "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", "title": null }, { "PMCID": null, "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15922621", "title": null }, { "PMCID": null, "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16458531", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", "title": null }, { "PMCID": null, "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", - "doi": null, + "doi": "10.1016/0020-7381(83)85053-0", "pubmed_id": null, "title": null }, @@ -869,7 +869,7 @@ "PMCID": null, "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. Model. 1999;17:57\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10660911", "title": null }, { @@ -887,10 +887,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N.B. Error analysis and propagation in metabolomics data analysis. Comp. Struct Biotech. J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { diff --git a/tests/testing_files/intermediate_results/ref_search/no_Crossref/running_pubs2.json b/tests/testing_files/intermediate_results/ref_search/no_Crossref/running_pubs2.json index c8d02f2..c79bd61 100644 --- a/tests/testing_files/intermediate_results/ref_search/no_Crossref/running_pubs2.json +++ b/tests/testing_files/intermediate_results/ref_search/no_Crossref/running_pubs2.json @@ -46,7 +46,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1007/978-1-4939-1258-2_11", + "doi": "10.1007/978-1-4939-1258-2_11", "grants": [ "1R01CA118434-01A2", "5P20RR018733", @@ -79,14 +79,14 @@ "PMCID": null, "citation": "Schlotterbeck G, Ross A, Dieterle F, Senn H. Metabolic profiling technologies for biomarker discovery in biomedicine and drug development. Pharmacogenomics. 2006;7:1055\u20131075.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17054416", "title": null }, { "PMCID": null, "citation": "Oresic M, Vidal-Puig A, Hanninen V. Metabolomic approaches to phenotype characterization and applications to complex diseases. Expert Review of Molecular Diagnostics. 2006;6:575\u2013585.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16824031", "title": null }, { @@ -97,24 +97,24 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2724746", "citation": "Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457:910\u2013914.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19212411", "title": null }, { "PMCID": null, "citation": "Griffiths William J., T. K., Wang Yuqin, Kohl Matthias, Enot David P., Deigner H-P. Targeted Metabolomics for Biomarker Discovery. Angew. Chem. Int. Ed. 2010;49:5426\u20135446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20629054", "title": null }, { "PMCID": null, "citation": "Theodoridis G, Gika HG, Wilson ID. Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies. Mass Spectrom. Rev. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "21384411", "title": null }, { @@ -128,14 +128,14 @@ "PMCID": null, "citation": "Andrew Clayton T, Lindon JC, Cloarec O, Antti H, Charuel C, Hanton G, Provost J-P, Le Net J-L\u00d8, Baker D, Walley RJ, Everett JR, Nicholson JK. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature. 2006;440:1073\u20131077.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16625200", "title": null }, { "PMCID": null, "citation": "Harrigan GG, Brackett DJ, Boros LG. Medicinal chemistry, metabolic profiling and drug target discovery: A role for metabolic profiling in reverse pharmacology and chemical genetics. Mini-Reviews in Medicinal Chemistry. 2005;5:13\u201320.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15638788", "title": null }, { @@ -149,133 +149,133 @@ "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN. Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metab. Rev. 2006;38:707\u2013732.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17145697", "title": null }, { "PMCID": null, "citation": "Robertson DG. Metabonomics in toxicology: A review. Toxicological Sciences. 2005;85:809\u2013822.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15689416", "title": null }, { "PMCID": null, "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15544433", "title": null }, { - "PMCID": null, + "PMCID": "PMC2140249", "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17786640", "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { "PMCID": null, "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19478804", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21466455", "title": null }, { - "PMCID": null, + "PMCID": "PMC3087304", "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21350847", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { "PMCID": null, "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16258367", "title": null }, { "PMCID": null, "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15611129", "title": null }, { - "PMCID": null, + "PMCID": "PMC2917841", "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20686576", "title": null }, { "PMCID": null, "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15663322", "title": null }, { @@ -286,122 +286,122 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM)) Molecular Cancer. 2009;8:41.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley HNB. Error Analysis and Propagation in Metabolomics Data Analysis. Comp Struct Biotech J. 2013;4:e201301006.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23667718", "title": null }, { "PMCID": null, "citation": "Fan TWM, Higashi RM, Lane AN, Jardetzky O. Combined use of proton NMR and gas chromatography-mass spectra for metabolite monitoring and in vivo proton NMR assignments. Biochimica et Biophysica Acta. 1986;882:154\u2013167.", "doi": null, - "pubmed_id": null, + "pubmed_id": "3011112", "title": null }, { "PMCID": null, "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", "doi": null, - "pubmed_id": null, + "pubmed_id": "11062433", "title": null }, { - "PMCID": null, + "PMCID": "PMC3746802", "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22608776", "title": null }, { - "PMCID": null, + "PMCID": "PMC3430598", "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study. BMC Genomics. 2012;13:334.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22823888", "title": null }, { - "PMCID": null, + "PMCID": "PMC3384197", "citation": "Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, Phang JM. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci U S A. 2012;109:8983\u20138988.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22615405", "title": null }, { - "PMCID": null, + "PMCID": "PMC3703516", "citation": "Dong C, Yuan T, Wu Y, Wang Y, Fan TW, Miriyala S, Lin Y, Yao J, Shi J, Kang T, Lorkiewicz P, St Clair D, Hung MC, Evers BM, Zhou BP. Loss of FBP1 by Snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 2013;23:316\u2013331.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23453623", "title": null }, { - "PMCID": null, + "PMCID": "PMC2903070", "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20631920", "title": null }, { - "PMCID": null, + "PMCID": "PMC2475696", "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18364355", "title": null }, { "PMCID": null, "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15994921", "title": null }, { "PMCID": null, "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9612242", "title": null }, { "PMCID": null, "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16317166", "title": null }, { - "PMCID": null, + "PMCID": "PMC3109995", "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21666826", "title": null }, { "PMCID": null, "citation": "Yang TH, Wittmann C, Heinzle E. Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum. Metab Eng. 2006;8:432\u2013446.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16750927", "title": null }, { - "PMCID": null, + "PMCID": "PMC2952699", "citation": "Paul Lee W-N, P. N. W., Xuc Jun, Liang Go Vay. Tracer-based Metabolomics: Concepts and Practices. Clinical Biochemistry. 2010;43:1269\u20131277.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20713038", "title": null }, { @@ -419,38 +419,38 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3471671", "citation": "Fan TW, Lorkiewicz P, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol Ther. 2012;133:366\u2013391.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22212615", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37.", "doi": null, - "pubmed_id": null, + "pubmed_id": "21627825", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Fan TWM, Colmer TD, Lane AN, Higashi RM. Determination of Metabolites by Proton Nmr and Gc Analysis for Organic Osmolytes in Crude Tissue Extracts. Analytical Biochemistry. 1993;214:260\u2013271.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8250233", "title": null }, { "PMCID": null, "citation": "Gradwell MJ, Fan TWM, Lane AN. Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional 1H-31P NMR heteronuclear total correlation spectroscopy (hetero TOCSY) Analytical Biochemistry. 1998;263:139\u2013149.", "doi": null, - "pubmed_id": null, + "pubmed_id": "9799525", "title": null }, { @@ -475,17 +475,17 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { - "PMCID": null, + "PMCID": "PMC3282107", "citation": "Yuneva MO, Fan TW-M, Higashi RM, Allen TA, Balakrishnan A, Goga A, Ferraris DV, Tsukamoto T, Wang C, Seo Y, Chen X, Bishop JM. The Metabolic Profile of Tumors Depends on Both the Responsible Genetic Lesion and Tissue Type Cell Metab. 2012;15:157\u2013170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22326218", "title": null }, { @@ -496,10 +496,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2847149", "citation": "Allwood JW, Erban A, de Koning S, Dunn WB, Luedemann A, Lommen A, Kay L, Loscher R, Kopka J, Goodacre R. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", "doi": null, - "pubmed_id": null, + "pubmed_id": "20376177", "title": null }, { @@ -513,91 +513,91 @@ "PMCID": null, "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16448047", "title": null }, { "PMCID": null, "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 2005;22:1155\u20131169.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16240456", "title": null }, { "PMCID": null, "citation": "Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, Goodacre R. Global Metabolic Profiling of Escherichia coli Cultures: an Evaluation of Methods for Quenching and Extraction of Intracellular Metabolites. Anal. Chem. 2008;80:2939\u20132948.", "doi": null, - "pubmed_id": null, + "pubmed_id": "18331064", "title": null }, { "PMCID": null, "citation": "Sellick CA, Hansen R, Maqsood AR, Dunn WB, Stephens GM, Goodacre R, Dickson AJ. Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells. Analytical Chemistry. 2009;81:174\u2013183.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19061395", "title": null }, { "PMCID": null, "citation": "Bolten CJ, Kiefer P, Letisse F, Portais JC, Wittmann C. Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17411014", "title": null }, { "PMCID": null, "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", "doi": null, - "pubmed_id": null, + "pubmed_id": "1514678", "title": null }, { "PMCID": null, "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12103361", "title": null }, { "PMCID": null, "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", "doi": null, - "pubmed_id": null, + "pubmed_id": "12009699", "title": null }, { "PMCID": null, "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17630720", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { - "PMCID": null, + "PMCID": "PMC3501132", "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. Metabolomics. 2012 In press.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23175637", "title": null }, { - "PMCID": null, + "PMCID": "PMC3345194", "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJ, Lorkiewicz PK, Higashi RM, Fan TW, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", "doi": null, - "pubmed_id": null, + "pubmed_id": "22225880", "title": null }, { - "PMCID": null, + "PMCID": "PMC4486296", "citation": "Fan TW-M, Tan JL, McKinney MM, Lane AN. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells. Metabolomics. 2012;8:517\u2013527.", "doi": null, - "pubmed_id": null, + "pubmed_id": "26146495", "title": null }, { @@ -608,45 +608,45 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane AN, Fan TW-M, Xie X, Moseley HN, Higashi RM. Stable isotope analysis of lipid biosynthesis by high resolution mass spectrometry and NMR Anal. Chim. Acta. 2009;651:201\u2013208.", "doi": null, - "pubmed_id": null, + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC3477816", "citation": "Lorkiewicz P, Higashi RM, Lane AN, Fan TWM. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8:930\u2013939.", "doi": null, - "pubmed_id": null, + "pubmed_id": "23101002", "title": null }, { "PMCID": null, "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Biophysical Tools for Biologists. 2008;84:541\u2013588.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17964943", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Selenocysteine. Annual Review of Biochemistry. 1996;65:83\u2013100.", "doi": null, - "pubmed_id": null, + "pubmed_id": "8811175", "title": null }, { "PMCID": null, "citation": "Stadtman TC. Reactive Oxygen Species: From Radiation to Molecular Biology. NEW YORK ACAD SCIENCES; New York: 2000. Selenium biochemistry - Mammalian selenoenzymes; pp. 399\u2013402.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10863556", "title": null }, { - "PMCID": null, + "PMCID": "PMC1794290", "citation": "Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A. 2007;104:1777\u20131782.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17267599", "title": null } ], @@ -684,7 +684,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.3390/metabo3040853", + "doi": "10.3390/metabo3040853", "grants": [ "P20 GM103436", "P20 RR016481", @@ -735,126 +735,126 @@ { "PMCID": null, "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", - "doi": null, - "pubmed_id": null, + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", "title": null }, { - "PMCID": null, + "PMCID": "PMC2717907", "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", "title": null }, { - "PMCID": null, + "PMCID": "PMC2757635", "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", - "doi": null, - "pubmed_id": null, + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", "title": null }, { - "PMCID": null, + "PMCID": "PMC2848236", "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", "title": null }, { "PMCID": null, "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", "title": null }, { - "PMCID": null, + "PMCID": "PMC3126751", "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", "title": null }, { "PMCID": null, "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", "title": null }, { "PMCID": null, "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", - "doi": null, - "pubmed_id": null, + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", "title": null }, { "PMCID": null, "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10362629", "title": null }, { "PMCID": null, "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", "title": null }, { - "PMCID": null, + "PMCID": "PMC2041839", "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", "doi": null, - "pubmed_id": null, + "pubmed_id": "17583532", "title": null }, { "PMCID": null, "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", "title": null }, { "PMCID": null, "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", "title": null }, { "PMCID": null, "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", "doi": null, - "pubmed_id": null, + "pubmed_id": "15922621", "title": null }, { "PMCID": null, "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", - "doi": null, - "pubmed_id": null, + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", "doi": null, - "pubmed_id": null, + "pubmed_id": "16458531", "title": null }, { "PMCID": null, "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", - "doi": null, - "pubmed_id": null, + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", "title": null }, { "PMCID": null, "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", - "doi": null, + "doi": "10.1016/0020-7381(83)85053-0", "pubmed_id": null, "title": null }, @@ -869,7 +869,7 @@ "PMCID": null, "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. Model. 1999;17:57\u201361.", "doi": null, - "pubmed_id": null, + "pubmed_id": "10660911", "title": null }, { @@ -887,10 +887,10 @@ "title": null }, { - "PMCID": null, + "PMCID": "PMC3647477", "citation": "Moseley H.N.B. Error analysis and propagation in metabolomics data analysis. Comp. Struct Biotech. 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Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -1274,98 +1274,98 @@ { "PMCID": null, "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -1379,28 +1379,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -1414,42 +1414,42 @@ { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -1463,21 +1463,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -1532,7 +1532,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", + "doi": "10.1038/s41597-023-02281-1", "grants": [ "P42 ES007380", "2020026" @@ -1556,14 +1556,14 @@ { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -1591,63 +1591,63 @@ { "PMCID": null, "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -1668,21 +1668,21 @@ { "PMCID": null, "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -1696,14 +1696,14 @@ { "PMCID": null, "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -1717,7 +1717,7 @@ { "PMCID": null, "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -1731,21 +1731,21 @@ { "PMCID": null, "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -1766,14 +1766,14 @@ { "PMCID": null, "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -1811,7 +1811,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", + "doi": "10.1186/s12859-023-05208-0", "grants": [ "2020026", "R03OD030603" @@ -1847,21 +1847,21 @@ { "PMCID": null, "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", + "doi": "10.1002/pro.3715", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", + "doi": "10.1093/nar/gkaa970", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", + "doi": "10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", "pubmed_id": null, "title": null }, @@ -1882,7 +1882,7 @@ { "PMCID": null, "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", + "doi": "10.1007/978-1-4842-4501-9_23", "pubmed_id": null, "title": null }, @@ -1903,7 +1903,7 @@ { "PMCID": null, "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, @@ -1917,14 +1917,14 @@ { "PMCID": null, "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": "https://doi.org/10.5281/zenodo.7482523", + "doi": "10.5281/zenodo.7482523", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", + "doi": "10.1093/bioinformatics/btp163", "pubmed_id": null, "title": null }, @@ -1962,7 +1962,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", + "doi": "10.1186/s12859-023-05423-9", "grants": [ "P42 ES007380", "2020026", @@ -2001,35 +2001,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -2071,14 +2071,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", + "doi": "10.1016/j.cbpa.2016.12.024", "pubmed_id": null, "title": null }, @@ -2092,7 +2092,7 @@ { "PMCID": null, "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", + "doi": "10.1093/gigascience/giab060", "pubmed_id": null, "title": null }, @@ -2106,14 +2106,14 @@ { "PMCID": null, "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", + "doi": "10.1107/S0021889809008784", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -2176,7 +2176,7 @@ ], "conclusions": null, "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", + "doi": "10.1289/ehp11484", "grants": [], "journal": "Environmental health perspectives", "keywords": [], @@ -2350,7 +2350,7 @@ { "PMCID": null, "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, @@ -2504,7 +2504,7 @@ { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, @@ -2595,273 +2595,273 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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"doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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"doi": "https://doi.org/10.1038/s41374-021-00631-4", + "doi": "10.1038/s41374-021-00631-4", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/1471-2105-7-234", + "doi": "10.1186/1471-2105-7-234", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.analchem.9b00748", + "doi": "10.1021/acs.analchem.9b00748", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.ymeth.2004.03.015", + "doi": "10.1016/j.ymeth.2004.03.015", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/mas.20108", + "doi": "10.1002/mas.20108", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.aca.2017.04.014", + "doi": "10.1016/j.aca.2017.04.014", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac3018795", + "doi": "10.1021/ac3018795", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac1011574", + "doi": "10.1021/ac1011574", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.pharmthera.2011.12.007", + "doi": "10.1016/j.pharmthera.2011.12.007", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/1741-7007-9-37", + "doi": "10.1186/1741-7007-9-37", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1172/JCI72873", + "doi": "10.1172/JCI72873", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-017-1250-7", + "doi": "10.1007/s11306-017-1250-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12859-019-3096-7", + "doi": "10.1186/s12859-019-3096-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/metabo10030118", + "doi": "10.3390/metabo10030118", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1426-9", + "doi": "10.1007/s11306-018-1426-9", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/metabo10030122", + "doi": "10.3390/metabo10030122", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/metabo11110740", + "doi": "10.3390/metabo11110740", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.5936/csbj.201301006", + "doi": "10.5936/csbj.201301006", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/biomet/42.1-2.58", + "doi": "10.1093/biomet/42.1-2.58", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/ac00278a027", + "doi": "10.1021/ac00278a027", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pcbi.1003118", + "doi": "10.1371/journal.pcbi.1003118", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", + "doi": "10.1016/j.jbusres.2017.12.043", "pubmed_id": null, "title": "Open Science now: A systematic literature review for an integrated definition" }, { "PMCID": null, "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": "The FAIR Guiding Principles for scientific data management and stewardship" }, { "PMCID": null, "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" }, @@ -4210,35 +4210,35 @@ { "PMCID": null, "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", + "doi": "10.1007/s11306-007-0070-6", "pubmed_id": null, "title": "The metabolomics standards initiative (MSI)" }, { "PMCID": null, "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -4252,7 +4252,7 @@ { "PMCID": null, "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -4294,14 +4294,14 @@ { "PMCID": null, "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, diff --git a/tests/testing_files/publication_dict_Hunter_old.json b/tests/testing_files/publication_dict_Hunter_old.json deleted file mode 100644 index fd32434..0000000 --- a/tests/testing_files/publication_dict_Hunter_old.json +++ /dev/null @@ -1,4655 +0,0 @@ -{ - "https://aacrjournals.org/cancerres/article/83/7_Supplement/3673/719740": { - "PMCID": null, - "abstract": null, - "authors": [ - { - "affiliation": "kentucky", - "author_id": "Hunter Moseley", - "firstname": "Hunter", - "initials": null, - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": null, - "doi": null, - "grants": [], - "journal": null, - "keywords": null, - "methods": null, - "publication_date": { - "day": null, - "month": null, - "year": 2023 - }, - "pubmed_id": null, - "queried_sources": [ - "Google Scholar" - ], - "references": [], - "results": null, - "title": "Plk1 phosphorylation of PHGDH to regulate serine metabolism" - }, - "https://chemrxiv.org/engage/chemrxiv/article-details/62da093f13e3659590e0d5eb": { - "PMCID": null, - "abstract": null, - "authors": [ - { - "affiliation": "kentucky", - "author_id": "Hunter Moseley", - "firstname": "Hunter", - "initials": null, - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": null, - "doi": null, - "grants": [], - "journal": null, - "keywords": null, - "methods": null, - "publication_date": { - "day": null, - "month": null, - "year": 2022 - }, - "pubmed_id": null, - "queried_sources": [ - "Google Scholar" - ], - "references": [], - "results": null, - "title": "A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems" - }, - "https://doi.org/https://doi.org/10.1002/hep.32467": { - "PMCID": "PMC9489820", - "abstract": "Resolution of pathways that converge to induce deleterious effects in hepatic diseases, such as in the later stages, have potential antifibrotic effects that may improve outcomes. We aimed to explore whether humans and rodents display similar fibrotic signaling networks.\nWe assiduously mapped kinase pathways using 340 substrate targets, upstream bioinformatic analysis of kinase pathways, and over 2000 random sampling iterations using the PamGene PamStation kinome microarray chip technology. Using this technology, we characterized a large number of kinases with altered activity in liver fibrosis of both species. Gene expression and immunostaining analyses validated many of these kinases as bona fide signaling events. Surprisingly, the insulin receptor emerged as a considerable protein tyrosine kinase that is hyperactive in fibrotic liver disease in humans and rodents. Discoidin domain receptor tyrosine kinase, activated by collagen that increases during fibrosis, was another hyperactive protein tyrosine kinase in humans and rodents with fibrosis. The serine/threonine kinases found to be the most active in fibrosis were dystrophy type 1 protein kinase and members of the protein kinase family of kinases. We compared the fibrotic events over four models: humans with cirrhosis and three murine models with differing levels of fibrosis, including two models of fatty liver disease with emerging fibrosis. The data demonstrate a high concordance between human and rodent hepatic kinome signaling that focalizes, as shown by our network analysis of detrimental pathways.\nOur findings establish a comprehensive kinase atlas for liver fibrosis, which identifies analogous signaling events conserved among humans and rodents.", - "authors": [ - { - "affiliation": "Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, Ohio, USA.", - "firstname": "Justin F", - "initials": "JF", - "lastname": "Creeden" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky College of Medicine, Lexington, Kentucky, USA.", - "firstname": "Zachary A", - "initials": "ZA", - "lastname": "Kipp" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky College of Medicine, Lexington, Kentucky, USA.", - "firstname": "Mei", - "initials": "M", - "lastname": "Xu" - }, - { - "affiliation": "Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, Kentucky, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, Kentucky, USA.\nResource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, Kentucky, USA.", - "firstname": "Robert M", - "initials": "RM", - "lastname": "Flight" - }, - { - "affiliation": "Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, Kentucky, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, Kentucky, USA.\nResource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, Kentucky, USA.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, Kentucky, USA.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, Kentucky, USA.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky College of Medicine, Lexington, Kentucky, USA.", - "firstname": "Genesee J", - "initials": "GJ", - "lastname": "Martinez" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky College of Medicine, Lexington, Kentucky, USA.", - "firstname": "Wang-Hsin", - "initials": "WH", - "lastname": "Lee" - }, - { - "affiliation": "Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, Ohio, USA.", - "firstname": "Khaled", - "initials": "K", - "lastname": "Alganem" - }, - { - "affiliation": "Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, Ohio, USA.", - "firstname": "Ali S", - "initials": "AS", - "lastname": "Imami" - }, - { - "affiliation": "Department of Inflammation and Immunity, Cleveland Clinic, Cleveland, Ohio, USA.", - "firstname": "Megan R", - "initials": "MR", - "lastname": "McMullen" - }, - { - "affiliation": "Department of Inflammation and Immunity, Cleveland Clinic, Cleveland, Ohio, USA.", - "firstname": "Sanjoy", - "initials": "S", - "lastname": "Roychowdhury" - }, - { - "affiliation": "Division of Transplant and Hepatobiliary, Department of Surgery, The University of Kansas Medical Center, Kansas City, Kansas, USA.", - "firstname": "Atta M", - "initials": "AM", - "lastname": "Nawabi" - }, - { - "affiliation": "Strata Oncology, Ann Arbor, Michigan, USA.", - "firstname": "Jennifer A", - "initials": "JA", - "lastname": "Hipp" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky College of Medicine, Lexington, Kentucky, USA.\nDepartment of Pediatrics, University of Kentucky, Lexington, Kentucky, USA.", - "firstname": "Samir", - "initials": "S", - "lastname": "Softic" - }, - { - "affiliation": "Department of Internal Medicine and Liver Center, University of Kansas Medical Center, Kansas City, Kansas, USA.", - "firstname": "Steven A", - "initials": "SA", - "lastname": "Weinman" - }, - { - "affiliation": "Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, Ohio, USA.\nNeurosciences Institute, ProMedica, Toledo, Ohio, USA.", - "firstname": "Robert", - "initials": "R", - "lastname": "McCullumsmith" - }, - { - "affiliation": "Department of Inflammation and Immunity, Cleveland Clinic, Cleveland, Ohio, USA.\nDepartment of Gastroenterology and Hepatology, Center for Liver Disease Research, Cleveland Clinic, Cleveland, Ohio, USA.\nDepartment of Molecular Medicine, Case Western Reserve University, Cleveland, Ohio, USA.", - "firstname": "Laura E", - "initials": "LE", - "lastname": "Nagy" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky College of Medicine, Lexington, Kentucky, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, Kentucky, USA.\nBarnstable Brown Diabetes Center, University of Kentucky College of Medicine, Lexington, Kentucky, USA.", - "firstname": "Terry D", - "initials": "TD", - "lastname": "Hinds" - } - ], - "conclusions": null, - "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", - "grants": [ - "R01 MH121102", - "R01 AG057598", - "R01 DK121797", - "R01 MH107487", - "P30 CA177558", - "P50 AA024333" - ], - "journal": "Hepatology (Baltimore, Md.)", - "keywords": [], - "methods": null, - "publication_date": { - "day": 22, - "month": 3, - "year": 2022 - }, - "pubmed_id": "35313030", - "queried_sources": [ - "PubMed", - "Google Scholar" - ], - "references": [ - { - "PMCID": null, - "citation": "Roehlen N, Crouchet E, Baumert TF. Liver fibrosis: mechanistic concepts and therapeutic perspectives. Cells. 2020;9:875.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Schuppan D, Ashfaq\u2010Khan M, Yang AT, Kim YO. Liver fibrosis: direct antifibrotic agents and targeted therapies. Matrix Biol. 2018;68\u201369:435\u201351.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lee UE, Friedman SL. Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol. 2011;25:195\u2013206.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655\u201369.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eslam M, Sanyal AJ, George J, International Consensus P . MAFLD: a consensus\u2010driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158:1999\u20132014 e1991.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Stec DE, Gordon DM, Hipp JA, Hong S, Mitchell ZL, Franco NR, et al. Loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet\u2010induced obesity. Am J Physiol Regul Integr Comp Physiol. 2019;317:R733\u2013R745.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds TD Jr, Creeden JF, Gordon DM, Stec DF, Donald MC, Stec DE. Bilirubin nanoparticles reduce diet\u2010induced hepatic steatosis, improve fat utilization, and increase plasma beta\u2010hydroxybutyrate. Front Pharmacol. 2020;11:594574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Stec DE, Hinds TD Jr. Natural product heme oxygenase inducers as treatment for nonalcoholic fatty liver disease. Int J Mol Sci. 2020;21:9493.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hamoud AR, Weaver L, Stec DE, Hinds TD Jr. Bilirubin in the liver\u2010gut signaling axis. Trends Endocrinol Metab. 2018;29:140\u201350.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds TD Jr, Hosick PA, Hankins MW, Nestor\u2010Kalinoski A, Stec DE. Mice with hyperbilirubinemia due to Gilbert's Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am J Physiol Endocrinol Metab. 2017;312:E244\u2013E252.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds TD, Sodhi K, Meadows C, Fedorova L, Puri N, Kim DH, et al. Increased HO\u20101 levels ameliorate fatty liver development through a reduction of heme and recruitment of FGF21. Obesity (Silver Spring). 2014;22:705\u201312.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Weaver L, Hamoud AR, Stec DE, Hinds TD Jr. Biliverdin reductase and bilirubin in hepatic disease. Am J Physiol Gastrointest Liver Physiol. 2018;314:G668\u2013G676.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Constandinou C, Henderson N, Iredale JP. Modeling liver fibrosis in rodents. Methods Mol Med. 2005;117:237\u201350.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pritchard MT, Nagy LE. Hepatic fibrosis is enhanced and accompanied by robust oval cell activation after chronic carbon tetrachloride administration to Egr\u20101\u2010deficient mice. Am J Pathol. 2010;176:2743\u201352.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc: Ser B (Methodol). 1995;57:289\u2013300.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Frangogiannis N. Transforming growth factor\u2010beta in tissue fibrosis. J Exp Med. 2020;217:e20190103.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Cai X, Li Z, Zhang Q, Qu Y, Xu M, Wan X, et al. CXCL6\u2010EGFR\u2010induced Kupffer cells secrete TGF\u2010beta1 promoting hepatic stellate cell activation via the SMAD2/BRD4/C\u2010MYC/EZH2 pathway in liver fibrosis. J Cell Mol Med. 2018;22:5050\u201361.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Li H\u2010G, You P\u2010T, Xia YU, Cai YU, Tu Y\u2010J, Wang M\u2010H, et al. Yu Gan long ameliorates hepatic fibrosis by inhibiting PI3K/AKT, Ras/ERK and JAK1/STAT3 signaling pathways in CCl4\u2010induced liver fibrosis rats. Curr Med Sci. 2020;40:539\u201347.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Carpino G, Morini S, Ginannicorradini S, Franchitto A, Merli M, Siciliano M, et al. Alpha\u2010SMA expression in hepatic stellate cells and quantitative analysis of hepatic fibrosis in cirrhosis and in recurrent chronic hepatitis after liver transplantation. Dig Liver Dis. 2005;37:349\u201356.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Borza CM, Pozzi A. Discoidin domain receptors in disease. Matrix Biol. 2014;34:185\u201392.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moll S, Desmouli\u00e8re A, Moeller MJ, Pache J\u2010C, Badi L, Arcadu F, et al. DDR1 role in fibrosis and its pharmacological targeting. Biochim Biophys Acta Mol Cell Res. 2019;1866:118474.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creeden JF, Alganem K, Imami AS, Henkel ND, Brunicardi FC, Liu S\u2010H, et al. Emerging kinase therapeutic targets in pancreatic ductal adenocarcinoma and pancreatic cancer desmoplasia. Int J Mol Sci. 2020;21:8823.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Svegliati\u2010Baroni G, Ridolfi F, Di Sario A, Casini A, Marucci L, Gaggiotti G, et al. Insulin and insulin\u2010like growth factor\u20101 stimulate proliferation and type I collagen accumulation by human hepatic stellate cells: differential effects on signal transduction pathways. Hepatology. 1999;29:1743\u201351.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Peterson SW, Angelico M, Masella R, Foster K, Gandin C, Cantafora A. Altered insulin receptor processing and membrane lipid composition in erythrocytes of cirrhotic patients. Ital J Gastroenterol. 1992;24:65\u201371.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Okada Y. Increased insulin binding to erythrocytes in chronic liver disease. Acta Med Okayama. 1981;35:155\u201364.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Petrides AS, Passlack W, Reinauer H, Stremmel W, Strohmeyer G. Insulin binding to erythrocytes in hyperinsulinemic patients with precirrhotic hemochromatosis and cirrhosis. Klin Wochenschr. 1987;65:873\u20138.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Teng CS, Ho PW, Yeung RT. Down\u2010regulation of insulin receptors in postnecrotic cirrhosis of liver. J Clin Endocrinol Metab. 1982;55:524\u201330.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Greco AV, Bertoli A, Ghirlanda G, Manna R, Altomonte L, Rebuzzi AG. Insulin resistance in liver cirrhosis: decreased insulin binding to circulating monocytes. Horm Metab Res. 1980;12:577\u201381.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Harewood MS, Proietto J, Dudley F, Alford FP. Insulin action and cirrhosis: insulin binding and lipogenesis in isolated adipocytes. Metabolism. 1982;31:1241\u20136.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ferguson D, Finck BN. Emerging therapeutic approaches for the treatment of NAFLD and type 2 diabetes mellitus. Nat Rev Endocrinol. 2021;17:484\u201395.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yen FS, Lai JN, Wei JC, Chiu LT, Hsu CC, Hou MC, et al. Is insulin the preferred treatment in persons with type 2 diabetes and liver cirrhosis? BMC Gastroenterol. 2021;21:263.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dongiovanni P, Meroni M, Baselli G, Bassani G, Rametta R, Pietrelli A, et al. Insulin resistance promotes Lysyl oxidase like 2 induction and fibrosis accumulation in non\u2010alcoholic fatty liver disease. Clin Sci (Lond). 2017;131:1301\u201315.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dongiovanni P, Valenti L, Rametta R, Daly AK, Nobili V, Mozzi E, et al. Genetic variants regulating insulin receptor signalling are associated with the severity of liver damage in patients with non\u2010alcoholic fatty liver disease. Gut. 2010;59:267\u201373.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Stechschulte LA, Wuescher L, Marino JS, Hill JW, Eng C, Hinds TD Jr. Glucocorticoid receptor beta stimulates Akt1 growth pathway by attenuation of PTEN. J Biol Chem. 2014;289:17885\u201394.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Smedlund KB, Sanchez ER, Hinds TD Jr. FKBP51 and the molecular chaperoning of metabolism. Trends Endocrinol Metab. 2021;32:862\u201374.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Stec DE, Gordon DM, Nestor\u2010Kalinoski AL, Donald MC, Mitchell ZL, Creeden JF, et al. Biliverdin reductase A (BVRA) knockout in adipocytes induces hypertrophy and reduces mitochondria in white fat of obese mice. Biomolecules. 2020;10:387.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds TD Jr, Burns KA, Hosick PA, McBeth L, Nestor\u2010Kalinoski A, Drummond HA, et al. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator\u2010activated receptor (PPAR) alpha. J Biol Chem. 2016;291:25179\u201391.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "O'Brien L, Hosick PA, John K, Stec DE, Hinds TD Jr. Biliverdin reductase isozymes in metabolism. Trends Endocrinol Metab. 2015;26:212\u201320.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Cai CX, Buddha H, Castelino\u2010Prabhu S, Zhang Z, Britton RS, Bacon BR, et al. Activation of insulin\u2010PI3K/Akt\u2010p70S6K pathway in hepatic stellate cells contributes to fibrosis in nonalcoholic steatohepatitis. Dig Dis Sci. 2017;62:968\u201378.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Zhang F, Zhang Z, Kong D, Zhang X, Chen LI, Zhu X, et al. Tetramethylpyrazine reduces glucose and insulin\u2010induced activation of hepatic stellate cells by inhibiting insulin receptor\u2010mediated PI3K/AKT and ERK pathways. Mol Cell Endocrinol. 2014;382:197\u2013204.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mateus T, Martins F, Nunes A, Herdeiro MT, Rebelo S. Metabolic alterations in myotonic dystrophy type 1 and their correlation with lipin. Int J Environ Res Public Health. 2021;18:1794.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Llagostera E, Catalucci D, Marti L, Liesa M, Camps M, Ciaraldi TP, et al. Role of myotonic dystrophy protein kinase (DMPK) in glucose homeostasis and muscle insulin action. PLoS One. 2007;2:e1134.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Bhardwaj RR, Duchini A. Non\u2010alcoholic steatohepatitis in myotonic dystrophy: DMPK gene mutation, insulin resistance and development of steatohepatitis. Case Rep Gastroenterol. 2010;4:100\u20133.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wahlang B, McClain C, Barve S, Gobejishvili L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell Signal. 2018;49:105\u201315.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang J, Zhang X, Yi L, Yang L, Wang WE, Zeng C, et al. Hepatic PKA inhibition accelerates the lipid accumulation in liver. Nutr Metab (Lond). 2019;16:69.", - "doi": null, - "pubmed_id": null, - "title": null - } - ], - "results": null, - "title": "Hepatic kinome atlas: An in-depth identification of kinase pathways in liver fibrosis of humans and rodents." - }, - "https://doi.org/https://doi.org/10.1038/s41467-023-35784-x": { - "PMCID": "PMC9859827", - "abstract": "Inhibitors of the Polycomb Repressive Complex 2 (PRC2) histone methyltransferase EZH2 are approved for certain cancers, but realizing their wider utility relies upon understanding PRC2 biology in each cancer system. Using a genetic model to delete Ezh2 in KRAS-driven lung adenocarcinomas, we observed that Ezh2 haplo-insufficient tumors were less lethal and lower grade than Ezh2 fully-insufficient tumors, which were poorly differentiated and metastatic. Using three-dimensional cultures and in vivo experiments, we determined that EZH2-deficient tumors were vulnerable to H3K27 demethylase or BET inhibitors. PRC2 loss/inhibition led to de-repression of FOXP2, a transcription factor that promotes migration and stemness, and FOXP2 could be suppressed by BET inhibition. Poorly differentiated human lung cancers were enriched for an H3K27me3-low state, representing a subtype that may benefit from BET inhibition as a single therapy or combined with additional EZH2 inhibition. These data highlight diverse roles of PRC2 in KRAS-driven lung adenocarcinomas, and demonstrate the utility of three-dimensional cultures for exploring epigenetic drug sensitivities for cancer.", - "authors": [ - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.\nDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, 510060, Guangzhou, P. R. China.", - "firstname": "Fan", - "initials": "F", - "lastname": "Chen" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Aria L", - "initials": "AL", - "lastname": "Byrd" - }, - { - "affiliation": "Department of Internal Medicine, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Jinpeng", - "initials": "J", - "lastname": "Liu" - }, - { - "affiliation": "Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY, 40536, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Robert M", - "initials": "RM", - "lastname": "Flight" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Tanner J", - "initials": "TJ", - "lastname": "DuCote" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Kassandra J", - "initials": "KJ", - "lastname": "Naughton" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Xiulong", - "initials": "X", - "lastname": "Song" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Abigail R", - "initials": "AR", - "lastname": "Edgin" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Alexsandr", - "initials": "A", - "lastname": "Lukyanchuk" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Danielle T", - "initials": "DT", - "lastname": "Dixon" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Christian M", - "initials": "CM", - "lastname": "Gosser" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Dave-Preston", - "initials": "DP", - "lastname": "Esoe" - }, - { - "affiliation": "Markey Cancer Center Biostatistics and Bioinformatics Shared Resource Facility, Lexington, KY, 40536, USA.", - "firstname": "Rani D", - "initials": "RD", - "lastname": "Jayswal" - }, - { - "affiliation": "Department of Hematology/Oncology, Boston Children's Hospital, Boston, MA, 02115, USA.", - "firstname": "Stuart H", - "initials": "SH", - "lastname": "Orkin" - }, - { - "affiliation": "Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY, 40536, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - }, - { - "affiliation": "Department of Internal Medicine, University of Kentucky, Lexington, KY, 40536, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Chi", - "initials": "C", - "lastname": "Wang" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA. cfbrainson@uky.edu.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA. cfbrainson@uky.edu.", - "firstname": "Christine Fillmore", - "initials": "CF", - "lastname": "Brainson" - } - ], - "conclusions": null, - "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41467-023-35784-x", - "grants": [ - "133123-RSG-19-081-01-TBG", - "GM121327", - "P30 CA177558", - "R01 CA237643", - "ES007266-30" - ], - "journal": "Nature communications", - "keywords": [], - "methods": null, - "publication_date": { - "day": 21, - "month": 1, - "year": 2023 - }, - "pubmed_id": "36670102", - "queried_sources": [ - "PubMed", - "Google Scholar" - ], - "references": [ - { - "PMCID": null, - "citation": "Bracken AP, Helin K. Polycomb group proteins: navigators of lineage pathways led astray in cancer. Nat. Rev. Cancer. 2009;9:773. doi: 10.1038/nrc2736.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat. Med. 2016;22:128\u2013134. doi: 10.1038/nm.4036.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Zhang H, et al. Oncogenic deregulation of EZH2 as an opportunity for targeted therapy in lung cancer. Cancer Discov. 2016;6:1006\u20131021. doi: 10.1158/2159-8290.CD-16-0164.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kleer CG, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl Acad. Sci. USA. 2003;100:11606\u201311611. doi: 10.1073/pnas.1933744100.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kikuchi J, et al. Distinctive expression of the polycomb group proteins Bmi1 polycomb ring finger oncogene and enhancer of zeste homolog 2 in nonsmall cell lung cancers and their clinical and clinicopathologic significance. Cancer. 2010;116:3015\u20133024. doi: 10.1002/cncr.25128.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Chen X, et al. High expression of trimethylated histone H3 at lysine 27 predicts better prognosis in non-small cell lung cancer. Int. J. Oncol. 2013;43:1467\u20131480. doi: 10.3892/ijo.2013.2062.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Holm K, et al. Global H3K27 trimethylation and EZH2 abundance in breast tumor subtypes. Mol. Oncol. 2012;6:494\u2013506. doi: 10.1016/j.molonc.2012.06.002.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Bae WK, et al. The methyltransferase EZH2 is not required for mammary cancer development, although high EZH2 and low H3K27me3 correlate with poor prognosis of ER-positive breast cancers. Mol. Carcinog. 2015;54:1172\u20131180. doi: 10.1002/mc.22188.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Zhang H, et al. Lkb1 inactivation drives lung cancer lineage switching governed by polycomb repressive complex 2. Nat. Commun. 2017;8:14922\u201314922. doi: 10.1038/ncomms14922.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Serresi M, et al. Polycomb repressive complex 2 is a barrier to KRAS-driven inflammation and epithelial-mesenchymal transition in non-small-cell lung cancer. Cancer Cell. 2016;29:17\u201331. doi: 10.1016/j.ccell.2015.12.006.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Serresi M, et al. Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. J. Exp. Med. 2018;215:3115\u20133135. doi: 10.1084/jem.20180801.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang Y, et al. Ezh2 acts as a tumor suppressor in Kras-driven lung adenocarcinoma. Int. J. Biol. Sci. 2017;13:652\u2013659. doi: 10.7150/ijbs.19108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hoy SM. Tazemetostat: first approval. Drugs. 2020;80:513\u2013521. doi: 10.1007/s40265-020-01288-x.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang D, et al. Targeting EZH2 reprograms intratumoral regulatory T cells to enhance cancer immunity. Cell Rep. 2018;23:3262\u20133274. doi: 10.1016/j.celrep.2018.05.050.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Shin, D. S., Park, K., Garon, E. & Dubinett, S. Targeting EZH2 to overcome the resistance to immunotherapy in lung cancer. Semin. Oncol.49, 306\u2013318 (2022).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "De Raedt T, et al. PRC2 loss amplifies Ras-driven transcription and confers sensitivity to BRD4-based therapies. Nature. 2014;514:247\u2013251. doi: 10.1038/nature13561.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Piunti A, et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 2017;23:493\u2013500. doi: 10.1038/nm.4296.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mohammad F, et al. EZH2 is a potential therapeutic target for H3K27M-mutant pediatric gliomas. Nat. Med. 2017;23:483\u2013492. doi: 10.1038/nm.4293.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Zhang Y, et al. Combination of EZH2 inhibitor and BET inhibitor for treatment of diffuse intrinsic pontine glioma. Cell Biosci. 2017;7:56. doi: 10.1186/s13578-017-0184-0.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Watarai H, et al. Impact of H3K27 demethylase inhibitor GSKJ4 on NSCLC cells alone and in combination with metformin. Anticancer Res. 2016;36:6083\u20136092. doi: 10.21873/anticanres.11198.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yan N, et al. GSKJ4, an H3K27me3 demethylase inhibitor, effectively suppresses the breast cancer stem cells. Exp. Cell Res. 2017;359:405\u2013414. doi: 10.1016/j.yexcr.2017.08.024.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dalvi MP, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep. 2017;19:1669\u20131684. doi: 10.1016/j.celrep.2017.04.077.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Cardoso WV, L\u00fc J. Regulation of early lung morphogenesis: questions, facts and controversies. Development. 2006;133:1611\u20131624. doi: 10.1242/dev.02310.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567\u2013582. doi: 10.1016/j.cell.2008.01.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Shu W, Yang H, Zhang L, Lu MM, Morrisey EE. Characterization of a new subfamily of winged-helix/forkhead (Fox) genes that are expressed in the lung and act as transcriptional repressors. J. Biol. Chem. 2001;276:27488\u201327497. doi: 10.1074/jbc.M100636200.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "McCauley KB, et al. Single-cell transcriptomic profiling of pluripotent stem cell-derived SCGB3A2\u2009+\u2009airway epithelium. Stem Cell Rep. 2018;10:1579\u20131595. doi: 10.1016/j.stemcr.2018.03.013.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hawkins F, et al. Prospective isolation of NKX2-1-expressing human lung progenitors derived from pluripotent stem cells. J. Clin. Investig. 2017;127:2277\u20132294. doi: 10.1172/JCI89950.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Shu W, et al. Foxp2 and Foxp1 cooperatively regulate lung and esophagus development. Development. 2007;134:1991\u20132000. doi: 10.1242/dev.02846.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Zhou B, et al. Foxp2 inhibits Nkx2.1-mediated transcription of SP-C via interactions with the Nkx2.1 homeodomain. Am. J. Respir. Cell Mol. Biol. 2008;38:750\u2013758. doi: 10.1165/rcmb.2007-0350OC.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Weng JS, et al. MCRIP1 promotes the expression of lung-surfactant proteins in mice by disrupting CtBP-mediated epigenetic gene silencing. Commun. Biol. 2019;2:227. doi: 10.1038/s42003-019-0478-3.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Li T, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509\u2013w514. doi: 10.1093/nar/gkaa407.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sturm G, et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019;35:i436\u2013i445. doi: 10.1093/bioinformatics/btz363.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Newman AM, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods. 2015;12:453\u2013457. doi: 10.1038/nmeth.3337.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA. 2005;102:15545\u201315550. doi: 10.1073/pnas.0506580102.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. doi: 10.4110/in.2018.18.e27.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Batlle E, Clevers H. Cancer stem cells revisited. Nat. Med. 2017;23:1124\u20131134. doi: 10.1038/nm.4409.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gerstein MB, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489:91\u2013100. doi: 10.1038/nature11245.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Delmore JE, et al. BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell. 2011;146:904\u2013917. doi: 10.1016/j.cell.2011.08.017.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Nagy \u00c1, Munk\u00e1csy G, Gy\u0151rffy B. Pancancer survival analysis of cancer hallmark genes. Sci. Rep. 2021;11:6047. doi: 10.1038/s41598-021-84787-5.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kim M, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat. Commun. 2019;10:3991. doi: 10.1038/s41467-019-11867-6.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Onishi T, Takashima T, Kurashige M, Ohshima K, Morii E. Mutually exclusive expression of EZH2 and H3K27me3 in non-small cell lung carcinoma. Pathol. Res. Pract. 2022;238:154071. doi: 10.1016/j.prp.2022.154071.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pellakuru LG, et al. Global levels of H3K27me3 track with differentiation in vivo and are deregulated by MYC in prostate cancer. Am. J. Pathol. 2012;181:560\u2013569. doi: 10.1016/j.ajpath.2012.04.021.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Zhu K, et al. Analysis of H3K27me3 expression and DNA methylation at CCGG sites in smoking and non-smoking patients with non-small cell lung cancer and their clinical significance. Oncol. Lett. 2018;15:6179\u20136188.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kim J, et al. Polycomb- and methylation-independent roles of EZH2 as a transcription activator. Cell Rep. 2018;25:2808\u20132820.e2804. doi: 10.1016/j.celrep.2018.11.035.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kim KH, et al. SWI/SNF-mutant cancers depend on catalytic and non-catalytic activity of EZH2. Nat. Med. 2015;21:1491\u20131496. doi: 10.1038/nm.3968.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Xu K, et al. EZH2 oncogenic activity in castration-resistant prostate cancer cells is polycomb-independent. Science. 2012;338:1465\u20131469. doi: 10.1126/science.1227604.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wei Y, et al. Loss of trimethylation at lysine 27 of histone H3 is a predictor of poor outcome in breast, ovarian, and pancreatic cancers. Mol. Carcinog. 2008;47:701\u2013706. doi: 10.1002/mc.20413.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ramirez RD, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res. 2004;64:9027\u20139034. doi: 10.1158/0008-5472.CAN-04-3703.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jackson EL, et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65:10280\u201310288. doi: 10.1158/0008-5472.CAN-05-2193.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Shen X, et al. EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Mol. Cell. 2008;32:491\u2013502. doi: 10.1016/j.molcel.2008.10.016.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114\u20132120. doi: 10.1093/bioinformatics/btu170.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinforma. 2011;12:323. doi: 10.1186/1471-2105-12-323.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u2013140. doi: 10.1093/bioinformatics/btp616.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "R_Core_Team. R: A Language and Environment for Statistical Computing. https://www.R-project.org/ (R, Foundation for Statistical Computing, Vienna, Austria, 2020).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sakai, R., Winand, R., Verbeiren, T., Moere, A. & Aerts, J. dendsort: modular leaf ordering methods for dendrogram representations in R. F1000 Research3, 10.12688/f1000research.4784.1 (2014).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight, R. M. et al. categoryCompare, an analytical tool based on feature annotations. Front. Genet.5, 10.3389/fgene.2014.00098 (2014).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "McLean CY, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 2010;28:495\u2013501. doi: 10.1038/nbt.1630.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sakai Y, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci. Transl. Med. 2011;3:86ra49. doi: 10.1126/scitranslmed.3002166.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang L, Jin Q, Lee JE, Su IH, Ge K. Histone H3K27 methyltransferase Ezh2 represses Wnt genes to facilitate adipogenesis. Proc. Natl Acad. Sci. USA. 2010;107:7317\u20137322. doi: 10.1073/pnas.1000031107.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Proia TA, et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell. 2011;8:149\u2013163. doi: 10.1016/j.stem.2010.12.007.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Chen F, et al. EZH2 inhibition confers PIK3CA-driven lung tumors enhanced sensitivity to PI3K inhibition. Cancer Lett. 2022;524:151\u2013160. doi: 10.1016/j.canlet.2021.10.010.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fillmore CM, et al. Estrogen expands breast cancer stem-like cells through paracrine FGF/Tbx3 signaling. Proc. Natl Acad. Sci. USA. 2010;107:21737\u201321742. doi: 10.1073/pnas.1007863107.", - "doi": null, - "pubmed_id": null, - "title": null - } - ], - "results": null, - "title": "Polycomb deficiency drives a FOXP2-high aggressive state targetable by epigenetic inhibitors." - }, - "https://doi.org/https://doi.org/10.1038/s41597-023-02277-x": { - "PMCID": "PMC10275912", - "abstract": "Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps.", - "authors": [ - { - "affiliation": "University of Kentucky, College of Engineering, Department of Civil Engineering, Lexington, Kentucky, USA.\nUniversity of Kentucky Superfund Research Center (UKSRC), Lexington, Kentucky, USA.", - "firstname": "Sweta", - "initials": "S", - "lastname": "Ojha" - }, - { - "affiliation": "University of Kentucky Superfund Research Center (UKSRC), Lexington, Kentucky, USA.", - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "affiliation": "University of Kentucky Superfund Research Center (UKSRC), Lexington, Kentucky, USA.\nUniversity of Kentucky, Department of Computer Science (Data Science Program), Lexington, Kentucky, USA.", - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "affiliation": "University of Kentucky Superfund Research Center (UKSRC), Lexington, Kentucky, USA.\nUniversity of Kentucky, Department of Molecular and Cellular Biochemistry, Lexington, Kentucky, USA.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - }, - { - "affiliation": "University of Kentucky, College of Engineering, Department of Civil Engineering, Lexington, Kentucky, USA. kellypennell@uky.edu.\nUniversity of Kentucky Superfund Research Center (UKSRC), Lexington, Kentucky, USA. kellypennell@uky.edu.", - "firstname": "Kelly G", - "initials": "KG", - "lastname": "Pennell" - } - ], - "conclusions": null, - "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", - "grants": [ - "P42 ES007380" - ], - "journal": "Scientific data", - "keywords": [], - "methods": null, - "publication_date": { - "day": 17, - "month": 6, - "year": 2023 - }, - "pubmed_id": "37328532", - "queried_sources": [ - "PubMed", - "ORCID", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Environmental Protection Agency (EPA), PFAS Strategic Roadmap: EPA\u2019s Commitments to Action 2021\u20132024. https://www.epa.gov/system/files/documents/2021-10/pfas-roadmap_final-508.pdf (2021).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gl\u00fcge J, et al. An overview of the uses of per-and polyfluoroalkyl substances (PFAS) Envir. Sci.-Proc. Imp. 2020;22:2345\u20132373.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Koch A, et al. Point source characterization of per-and polyfluoroalkyl substances (PFASs) and extractable organofluorine (EOF) in freshwater and aquatic invertebrates. Environ. Sci.-Proc. Imp. 2019;21:1887\u20131898.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Schroeder T, Bond D, Foley J. PFAS soil and groundwater contamination via industrial airborne emission and land deposition in SW Vermont and Eastern New York State, USA. Environ. Sci.-Proc. Imp. 2021;23:291\u2013301.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Thompson P. T., Ojha S., Powell C. D., Pennell K. G. & Moseley H. N. B. A proposed FAIR approach for disseminating geospatial information system maps. Accepted Sci. Data (2023).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", - "pubmed_id": null, - "title": null - } - ], - "results": null, - "title": "Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water." - }, - "https://doi.org/https://doi.org/10.1038/s41597-023-02281-1": { - "PMCID": "PMC10275873", - "abstract": "We present a draft Minimum Information About Geospatial Information System (MIAGIS) standard for facilitating public deposition of geospatial information system (GIS) datasets that follows the FAIR (Findable, Accessible, Interoperable and Reusable) principles. The draft MIAGIS standard includes a deposition directory structure and a minimum javascript object notation (JSON) metadata formatted file that is designed to capture critical metadata describing GIS layers and maps as well as their sources of data and methods of generation. The associated miagis Python package facilitates the creation of this MIAGIS metadata file and directly supports metadata extraction from both Esri JSON and GEOJSON GIS data formats plus options for extraction from user-specified JSON formats. We also demonstrate their use in crafting two example depositions of ArcGIS generated maps. We hope this draft MIAGIS standard along with the supporting miagis Python package will assist in establishing a GIS standards group that will develop the draft into a full standard for the wider GIS community as well as a future public repository for GIS datasets.", - "authors": [ - { - "affiliation": "University of Kentucky Superfund Research Center (UKSRC), Lexington, KY, USA.", - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "affiliation": "University of Kentucky Superfund Research Center (UKSRC), Lexington, KY, USA.\nUniversity of Kentucky, College of Engineering, Department of Civil Engineering, Lexington, KY, USA.", - "firstname": "Sweta", - "initials": "S", - "lastname": "Ojha" - }, - { - "affiliation": "University of Kentucky Superfund Research Center (UKSRC), Lexington, KY, USA.\nUniversity of Kentucky, Department of Computer Science (Data Science Program), Lexington, KY, USA.", - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "affiliation": "University of Kentucky Superfund Research Center (UKSRC), Lexington, KY, USA.\nUniversity of Kentucky, College of Engineering, Department of Civil Engineering, Lexington, KY, USA.", - "firstname": "Kelly G", - "initials": "KG", - "lastname": "Pennell" - }, - { - "affiliation": "University of Kentucky Superfund Research Center (UKSRC), Lexington, KY, USA. hunter.moseley@uky.edu.\nUniversity of Kentucky, Department of Molecular and Cellular Biochemistry, Lexington, KY, USA. hunter.moseley@uky.edu.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02281-1", - "grants": [ - "P42 ES007380" - ], - "journal": "Scientific data", - "keywords": [], - "methods": null, - "publication_date": { - "day": 17, - "month": 6, - "year": 2023 - }, - "pubmed_id": "37328607", - "queried_sources": [ - "PubMed", - "ORCID", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Bishop, B. W. & Hank, C. Measuring FAIR principles to inform fitness for use. (2018).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jacobsen A, et al. FAIR principles: interpretations and implementation considerations. MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info \u2026. 2020;2:10\u201329.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "National Academies of Sciences, E.; Medicine. Open science by design: Realizing a vision for 21st century research (2018).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Protein Data Bank the single global archive for 3D macromolecular structure data. Nucleic acids research. 2019;47:D520\u2013D528. doi: 10.1093/nar/gky949.", - "doi": "https://doi.org/10.1093/nar/gky949", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Clough E, Barrett T. Statistical genomics. New York, NY: Humana Press; 2016. The gene expression omnibus database; pp. 93\u2013110.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sud M, et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sarkans U, et al. From arrayexpress to biostudies. Nucleic Acids Research. 2021;49:D1502\u2013D1506. doi: 10.1093/nar/gkaa1062.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Brazma A, et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics. 2001;29:365\u2013371. doi: 10.1038/ng1201-365.", - "doi": "https://doi.org/10.1038/ng1201-365", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nature biotechnology. 2006;24:1471\u20131472. doi: 10.1038/nbt1206-1471.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell CD, Moseley HN. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "ArcGIS Online. Availabe online: https://arcgis.com/ (accessed on)", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "QGIS.org, QGIS Geographic Information System. QGIS Association. http://www.qgis.org, accessed on 04/27/2022 (2022).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kinkade D, Shepherd A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal. 2022;9:177\u2013186. doi: 10.1002/gdj3.120.", - "doi": "https://doi.org/10.1002/gdj3.120", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pampel H, et al. Making research data repositories visible: the re3data. org registry. PloS one. 2013;8:e78080. doi: 10.1371/journal.pone.0078080.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Degbelo A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science. 2022;36:1059\u20131099. doi: 10.1080/13658816.2021.1983579.", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Health, N. I. O. Final NIH policy for data management and sharing. NOT-OD-21-013. Vol NOT-OD-21-013. NIH Grants & Funding. Bethesda, MD: Office of The Director, National Institutes of Health (2020).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sicilia M-A, Garc\u00eda-Barriocanal E, S\u00e1nchez-Alonso S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science. 2017;106:54\u201360. doi: 10.1016/j.procs.2017.03.009.", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Zenedo. https://zenodo.org, Assessed on 04/27/2022. Availabe online: (accessed on)", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha, S., Thompson, P. T., Powell, C. D., Moseley, H. N. & Pennell, K. G. Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water. Scientific DataAccepted.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Thompson PT, Powell CD, Moseley HN. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one. 2022;17:e0277834. doi: 10.1371/journal.pone.0277834.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Committee, F. G. D. Content standard for digital geospatial metadata (CSDGM). http://www.fgdc.gov/standards/status/sub2_1.html (2000).", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Karschnick, O. et al. The UDK and ISO 19115 Standard. In Proceedings of EnviroInfo; pp. 475\u2013481.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha S, 2021. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha S, Moseley H, Powell CD, Pennell KG, Thompson PT. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha, S. ArcGIS map of Kentucky Water Lines. Availabe online: https://www.arcgis.com/home/webmap/viewer.html?webmap=06829286d1274d94b0d4d4be911502f1&extent=-91.8196,35.4102,-81.053,39.7525 (accessed on)", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", - "pubmed_id": null, - "title": null - } - ], - "results": null, - "title": "A proposed FAIR approach for disseminating geospatial information system maps." - }, - "https://doi.org/https://doi.org/10.1186/s12859-023-05208-0": { - "PMCID": "PMC9985241", - "abstract": "The Kyoto Encyclopedia of Genes and Genomes (KEGG) provides organized genomic, biomolecular, and metabolic information and knowledge that is reasonably current and highly useful for a wide range of analyses and modeling. KEGG follows the principles of data stewardship to be findable, accessible, interoperable, and reusable (FAIR) by providing RESTful access to their database entries via their web-accessible KEGG API. However, the overall FAIRness of KEGG is often limited by the library and software package support available in a given programming language. While R library support for KEGG is fairly strong, Python library support has been lacking. Moreover, there is no software that provides extensive command line level support for KEGG access and utilization.\nWe present kegg_pull, a package implemented in the Python programming language that provides better KEGG access and utilization functionality than previous libraries and software packages. Not only does kegg_pull include an application programming interface (API) for Python programming, it also provides a command line interface (CLI) that enables utilization of KEGG for a wide range of shell scripting and data analysis pipeline use-cases. As kegg_pull's name implies, both the API and CLI provide versatile options for pulling (downloading and saving) an arbitrary (user defined) number of database entries from the KEGG API. Moreover, this functionality is implemented to efficiently utilize multiple central processing unit cores as demonstrated in several performance tests. Many options are provided to optimize fault-tolerant performance across a single or multiple processes, with recommendations provided based on extensive testing and practical network considerations.\nThe new kegg_pull package enables new flexible KEGG retrieval use cases not available in previous software packages. The most notable new feature that kegg_pull provides is its ability to robustly pull an arbitrary number of KEGG entries with a single API method or CLI command, including pulling an entire KEGG database. We provide recommendations to users for the most effective use of kegg_pull according to their network and computational circumstances.", - "authors": [ - { - "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Erik", - "initials": "E", - "lastname": "Huckvale" - }, - { - "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA. hunter.moseley@uky.edu.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, 40536, USA. hunter.moseley@uky.edu.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, 40536, USA. hunter.moseley@uky.edu.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05208-0", - "grants": [ - "2020026", - "R03OD030603" - ], - "journal": "BMC bioinformatics", - "keywords": [ - "Application programming interface", - "Command line interface", - "KEGG", - "Python programming language", - "REST" - ], - "methods": null, - "publication_date": { - "day": 5, - "month": 3, - "year": 2023 - }, - "pubmed_id": "36870946", - "queried_sources": [ - "PubMed", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Kawashima S, Katayama T, Sato Y, Kanehisa M. KEGG API: a web service using SOAP/WSDL to Access the KEGG System. Genome Inform. 2003;14:673.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28:1947\u20131951. doi: 10.1002/pro.3715.", - "doi": "https://doi.org/10.1002/pro.3715", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021;49:D545\u2013D551. doi: 10.1093/nar/gkaa970.", - "doi": "https://doi.org/10.1093/nar/gkaa970", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "The kyoto encyclopedia of genes and genomes\u2014kegg. Yeast. 2000;1:48\u201355.", - "doi": "https://doi.org/10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fielding RT. Representational state transfer. Architectural Styles and the Design of Network-Based Software Architectures. Doctoral dissertation. University of California Irvine, Irvine, CA, USA; 2000.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Reitz K. requests. Computer software. Pypi; 2013.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Christudas B. cURL and Postman. In: Practical Microservices Architectural Patterns: Event-Based Java Microservices with Spring Boot and Spring Cloud. Berkeley, CA: Apress. 2019;847\u201355.", - "doi": "https://doi.org/10.1007/978-1-4842-4501-9_23", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "R Core Team, editor. R: A Language and environment for statistical computing. 2018.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Rossum GV, Drake FL. Python\u00a03\u00a0Reference\u00a0Manual. CreateSpace; 2009.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Tenenbaum D, Volkening J. KEGGREST. Computer software. Bioconductor Package Maintainer; 2022.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Castelli FM. 2022. KEGGutils v04.1. Computer software. Zenodo.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Cock PJA. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Computer software. PyPi; 2009.", - "doi": "https://doi.org/10.1093/bioinformatics/btp163", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Giampieri E. keggrest. Computer software. PyPi; 2013.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Castelli FM. KEGGutils v04.1. Computer software. 2022. Zenodo. https://doi.org/10.5281/zenodo.7482523.", - "doi": "https://doi.org/10.5281/zenodo.7482523", - "pubmed_id": null, - "title": null - } - ], - "results": "We present kegg_pull, a package implemented in the Python programming language that provides better KEGG access and utilization functionality than previous libraries and software packages. Not only does kegg_pull include an application programming interface (API) for Python programming, it also provides a command line interface (CLI) that enables utilization of KEGG for a wide range of shell scripting and data analysis pipeline use-cases. As kegg_pull's name implies, both the API and CLI provide versatile options for pulling (downloading and saving) an arbitrary (user defined) number of database entries from the KEGG API. Moreover, this functionality is implemented to efficiently utilize multiple central processing unit cores as demonstrated in several performance tests. Many options are provided to optimize fault-tolerant performance across a single or multiple processes, with recommendations provided based on extensive testing and practical network considerations.", - "title": "kegg_pull: a software package for the RESTful access and pulling from the Kyoto Encyclopedia of Gene and Genomes." - }, - "https://doi.org/https://doi.org/10.1186/s12859-023-05423-9": { - "PMCID": "PMC10364356", - "abstract": "An updated version of the mwtab Python package for programmatic access to the Metabolomics Workbench (MetabolomicsWB) data repository was released at the beginning of 2021. Along with updating the package to match the changes to MetabolomicsWB's 'mwTab' file format specification and enhancing the package's functionality, the included validation facilities were used to detect and catalog file inconsistencies and errors across all publicly available datasets in MetabolomicsWB.\nThe MetabolomicsWB File Status website was developed to provide continuous validation of MetabolomicsWB data files and a useful interface to all found inconsistencies and errors. This list of detectable issues/errors include format parsing errors, format compliance issues, access problems via MetabolomicsWB's REST interface, and other small inconsistencies that can hinder reusability. The website uses the mwtab Python package to pull down and validate each available analysis file and then generates an html report. The website is updated on a weekly basis. Moreover, the Python website design utilizes GitHub and GitHub.io, providing an easy to replicate template for implementing other metadata, virtual, and meta- repositories.\nThe MetabolomicsWB File Status website provides a metadata repository of validation metadata to promote the FAIR use of existing metabolomics datasets from the MetabolomicsWB data repository.", - "authors": [ - { - "affiliation": "Department of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, 40506, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40506, USA.\nSuperfund Research Center, University of Kentucky, Lexington, KY, 40506, USA.", - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY, 40506, USA. hunter.moseley@uky.edu.\nSuperfund Research Center, University of Kentucky, Lexington, KY, 40506, USA. hunter.moseley@uky.edu.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, 40506, USA. hunter.moseley@uky.edu.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, 40506, USA. hunter.moseley@uky.edu.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1186/s12859-023-05423-9", - "grants": [ - "P42 ES007380" - ], - "journal": "BMC bioinformatics", - "keywords": [ - "FAIR", - "Metabolomics Workbench", - "Metadata repository", - "Validation", - "Website", - "mwtab" - ], - "methods": null, - "publication_date": { - "day": 24, - "month": 7, - "year": 2023 - }, - "pubmed_id": "37482620", - "queried_sources": [ - "PubMed", - "ORCID", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "National institute of health. NIH common fund. National institutes of health office of strategic coordination - the common fund. Retrieved Feb 24, 2022, from https://commonfund.nih.gov/.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163. doi: 10.3390/metabo11030163.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "The metabolomics workbench file validator website. https://moseleybioinformaticslab.github.io/mwFileStatusWebsite/. Accessed 19 Feb 2022.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "MoseleyBioinformaticsLab/mwFileStatusWebsite GitHub Repository. https://github.com/MoseleyBioinformaticsLab/mwFileStatusWebsite. Accessed 19 Feb 2022.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "MoseleyBioinformaticsLab/mwtab GitHub repository. https://github.com/MoseleyBioinformaticsLab/mwtab. Accessed 19 Feb 2022.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "mwtab 1.2.4 Python package index webpage. https://pypi.org/project/mwtab/. Accessed 19 Feb 2022.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "mwtab Read the docs webpage. https://mwtab.readthedocs.io/. Accessed 19 Feb 2022.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. 10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363. doi: 10.1016/j.cbpa.2016.12.024.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Casasent T D, et al MetaBatch: MDACC standardized data metabolomics workbench tool. Retrieved Feb 24, 2022, from https://bioinformatics.mdanderson.org/StdMW/.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060. doi: 10.1093/gigascience/giab060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O\u2019Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440\u2013D444.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u2013384. doi: 10.1107/S0021889809008784.", - "doi": "https://doi.org/10.1107/S0021889809008784", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u2013D303. doi: 10.1093/nar/gkl971.", - "doi": "https://doi.org/10.1093/nar/gkl971", - "pubmed_id": null, - "title": null - } - ], - "results": "The MetabolomicsWB File Status website was developed to provide continuous validation of MetabolomicsWB data files and a useful interface to all found inconsistencies and errors. This list of detectable issues/errors include format parsing errors, format compliance issues, access problems via MetabolomicsWB's REST interface, and other small inconsistencies that can hinder reusability. The website uses the mwtab Python package to pull down and validate each available analysis file and then generates an html report. The website is updated on a weekly basis. Moreover, the Python website design utilizes GitHub and GitHub.io, providing an easy to replicate template for implementing other metadata, virtual, and meta- repositories.", - "title": "The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data." - }, - "https://doi.org/https://doi.org/10.1289/ehp11484": { - "PMCID": "PMC10289218", - "abstract": "Funding agencies, publishers, and other stakeholders are pushing environmental health science investigators to improve data sharing; to promote the findable, accessible, interoperable, and reusable (FAIR) principles; and to increase the rigor and reproducibility of the data collected. Accomplishing these goals will require significant cultural shifts surrounding data management and strategies to develop robust and reliable resources that bridge the technical challenges and gaps in expertise.\nIn this commentary, we examine the current state of managing data and metadata-referred to collectively as (meta)data-in the experimental environmental health sciences. We introduce new tools and resources based on \nWe discuss previous and ongoing efforts to improve (meta)data collection and curation. These include global efforts by the Functional Genomics Data Society to develop metadata collection tools such as the Investigation, Study, Assay (ISA) framework, and the Center for Expanded Data Annotation and Retrieval. We also conduct a case study of \nThe environmental health science community has played a key role in efforts to achieve the goals of the FAIR guiding principles and is well positioned to advance them further. We present a proposed framework to further promote these objectives and minimize the obstacles between data producers and data scientists to maximize the return on research investments. https://doi.org/10.1289/EHP11484.", - "authors": [ - { - "affiliation": "Biochemistry & Molecular Biology Department, Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan, USA.", - "firstname": "Rance", - "initials": "R", - "lastname": "Nault" - }, - { - "affiliation": "Division of Gastroenterology, Hepatology, and Nutrition, University of Louisville, Louisville, Kentucky, USA.", - "firstname": "Matthew C", - "initials": "MC", - "lastname": "Cave" - }, - { - "affiliation": "Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa, USA.", - "firstname": "Gabriele", - "initials": "G", - "lastname": "Ludewig" - }, - { - "affiliation": "Molecular and Cellular Biochemistry Department, University of Kentucky, Lexington, Kentucky, USA.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - }, - { - "affiliation": "Department of Civil Engineering, University of Kentucky, Lexington, Kentucky, USA.", - "firstname": "Kelly G", - "initials": "KG", - "lastname": "Pennell" - }, - { - "affiliation": "Biochemistry & Molecular Biology Department, Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan, USA.", - "firstname": "Tim", - "initials": "T", - "lastname": "Zacharewski" - }, - { - "affiliation": "Biochemistry & Molecular Biology Department, Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan, USA", - "firstname": "Rance", - "initials": null, - "lastname": "Nault" - }, - { - "affiliation": "Division of Gastroenterology, Hepatology, and Nutrition, University of Louisville, Louisville, Kentucky, USA", - "firstname": "Matthew C.", - "initials": null, - "lastname": "Cave" - }, - { - "affiliation": "Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa, USA", - "firstname": "Gabriele", - "initials": null, - "lastname": "Ludewig" - }, - { - "affiliation": "Department of Civil Engineering, University of Kentucky, Lexington, Kentucky, USA", - "firstname": "Kelly G.", - "initials": null, - "lastname": "Pennell" - }, - { - "affiliation": "Biochemistry & Molecular Biology Department, Institute for Integrative Toxicology, Michigan State University, East Lansing, Michigan, USA", - "firstname": "Tim", - "initials": null, - "lastname": "Zacharewski" - } - ], - "conclusions": null, - "copyrights": null, - "doi": "https://doi.org/10.1289/ehp11484", - "grants": [], - "journal": "Environmental health perspectives", - "keywords": [], - "methods": null, - "publication_date": { - "day": 23, - "month": 6, - "year": 2023 - }, - "pubmed_id": "37352010", - "queried_sources": [ - "PubMed", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Baker M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533(7604):452\u2013454, PMID: , 10.1038/533452a.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "NIH (National Institutes of Health) Office of Science Policy. 2020. Final NIH Policy for Data Management and Sharing: NOT-OD-21-013. https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-013.html.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "National Academies of Sciences Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: National Academies Press. 10.17226/25116 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "European Commission, Directorate-General for Research and Innovation. 2018. Turning FAIR into Reality: Final Report and Action Plan from the European Commission Expert Group on FAIR data. https://data.europa.eu/doi/10.2777/1524 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wellcome Trust. Open research. https://wellcome.org/what-we-do/our-work/open-research. [accessed 6 February 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Nemer M. 2020. Roadmap for Open Science. https://science.gc.ca/site/science/sites/default/files/attachments/2022/Roadmap-for-Open-Science.pdf [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Bhhatarai B, Walters WP, Hop C, Lanza G, Ekins S. 2019. Opportunities and challenges using artificial intelligence in ADME/Tox. Nat Mater 18(5):418\u2013422, PMID: , 10.1038/s41563-019-0332-5.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Boyles RR, Thessen AE, Waldrop A, Haendel MA. 2019. Ontology-based data integration for advancing toxicological knowledge. Curr Opin Toxicol 16:67\u201374, 10.1016/j.cotox.2019.05.005.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Chen X, Roberts R, Tong W, Liu Z. 2022. Tox-GAN: an artificial intelligence approach alternative to animal studies\u2013a case study with toxicogenomics. Toxicol Sci 186(2):242\u2013259, PMID: , 10.1093/toxsci/kfab157.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Brock J. 2019. \u201cA love letter to your future self\u201d: what scientists need to know about FAIR data. https://www.nature.com/nature-index/news-blog/what-scientists-need-to-know-about-fair-data. [accessed 6 February 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wallach JD, Boyack KW, Ioannidis JPA. 2018. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015\u20132017. PLoS Biol 16(11):e2006930, PMID: , 10.1371/journal.pbio.2006930.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ali B, Dahlhaus P. 2022. The role of FAIR data towards sustainable agricultural performance: a systematic literature review. Agriculture-Basel 12(2):309, 10.3390/agriculture12020309.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, et al. . 2008. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889\u2013896, PMID: , 10.1038/nbt.1411.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. . 2001. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29(4):365\u2013371, PMID: , 10.1038/ng1201-365.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "FAIRsharing.org. 2021. Minimum Information About a Microarray Experiment (MIAME). https://fairsharing.org/FAIRsharing.32b10v [accessed 26 September 2022].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "FAIRsharing.org. 2022. Minimal Information About a Cellular Assay (MIACA). https://fairsharing.org/FAIRsharing.7d0yv9 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "FAIRsharing.org. 2022. Minimal Information about a high throughput SEQuencing Experiment (MINSEQE). https://fairsharing.org/FAIRsharing.a55z32 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hofmann O, et al. . 2012. Toward interoperable bioscience data. Nat Genet 44(2):121\u2013126, PMID: , 10.1038/ng.1054.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sansone SA, Rocca-Serra P, Brandizi M, Brazma A, Field D, Fostel J, et al. . 2008. The first RSBI (ISA-TAB) workshop: \u201ccan a simple format work for complex studies?\u201d OMICS 12(2):143\u2013149, PMID: , 10.1089/omi.2008.0019.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sansone SA, Rocca-Serra P, Tong W, Fostel J, Morrison N, Jones AR, et al. . 2006. A strategy capitalizing on synergies: the Reporting Structure for Biological Investigation (RSBI) working group. OMICS 10(2):164\u2013171, PMID: , 10.1089/omi.2006.10.164.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kettner C, Field D, Sansone SA, Taylor C, Aerts J, Binns N, et al. . 2010. Meeting report from the second \u201cminimum information for biological and biomedical investigations\u201d (MIBBI) workshop. Stand Genomic Sci 3(3):259\u2013266, PMID: , 10.4056/sigs.147362.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moxon S, Solbrig H, Unni D, Jiao D, Bruskiewich R, Balhoff J, et al. . 2021. The Linked Data Modeling Language (LinkML): a general-purpose data modeling framework grounded in machine-readable semantics. In: CEUR Workshop Proceedings: 2021 International Conference on Biomedical Ontologies (ICBO 2021). 16\u201318 September 2021. Bozen-Bolzano, Italy, 148.\u2013.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gamble M, Goble C, Klyne G, Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago, Illinois, 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D, et al. . 2022. Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect 130(4):46001, PMID: , 10.1289/EHP10092.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flynn E, Chang A, Nugent BM, Altman R. 2021. Comprehensive assessment of smoking and sex related effects in publicly available gene expression data. bioRxiv. Preprint posted online September 29, 2021. 10.1101/2021.09.27.461968.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, et al. . 2020. Bringing big data to bear in environmental public health: challenges and recommendations. Front Artif Intell 3:31, PMID: , 10.3389/frai.2020.00031.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fostel JM, Burgoon L, Zwickl C, Lord P, Corton JC, Bushel PR, et al. . 2007. Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicol Sci 99(1):26\u201334, PMID: , 10.1093/toxsci/kfm090.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "FAIRsharing.org. 2021. Minimum Information About a Bioactive Entity (MIABE). https://fairsharing.org/FAIRsharing.dt7hn8 [accessed 15 February 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "FAIRsharing.org. 2022. Minimum Information About an Array-Based Toxicogenomics Experiment (MIAME/Tox). https://fairsharing.org/10.25504/FAIRsharing.zrmjr7 [accessed 4 November 2014].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "FAIRsharing.org. 2021. Minimal Information About T Cell Assays (MIATA). https://fairsharing.org/FAIRsharing.n7nqde [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Grulke CM, Williams AJ, Thillanadarajah I, Richard AM. 2019. EPA\u2019s DSSTox database: history of development of a curated chemistry resource supporting computational toxicology research. Comput Toxicol 12:100096, PMID: , 10.1016/j.comtox.2019.100096.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "O\u2019Connor MJ, Warzel DB, Martinez-Romero M, Hardi J, Willrett D, Egyedi AL, et al. . 2019. Unleashing the value of Common Data Elements through the CEDAR Workbench. AMIA Annu Symp Proc 2019:681\u2013690, PMID: .", - "doi": null, - "pubmed_id": null, - "title": "Unleashing the value of Common Data Elements through the CEDAR Workbench" - }, - { - "PMCID": null, - "citation": "Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. . 2020. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 48(D1):D440\u2013D444, PMID: , 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hufton A. Scientific Data\u2019s metadata specification. Scientificdataupdates: a blog from Scientific Data. https://blogs.nature.com/scientificdata/2014/01/08/scientific-datas-metadata-specification/ [accessed 24 May 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kim S, Hollinger H, Radke EG. 2022. Omics in environmental epidemiological studies of chemical exposures: a systematic evidence map. Environ Int 164:107243, PMID: , 10.1016/j.envint.2022.107243.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Waters M, Stasiewicz S, Merrick BA, Tomer K, Bushel P, Paules R, et al. . 2008. CEBS\u2013Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res 36(Database issue):D892\u2013D900, PMID: , 10.1093/nar/gkm755.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Watford S, Ly Pham L, Wignall J, Shin R, Martin MT, Friedman KP. 2019. ToxRefDB version 2.0: improved utility for predictive and retrospective toxicology analyses. Reprod Toxicol 89:145\u2013158, PMID: , 10.1016/j.reprotox.2019.07.012.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, et al. . 2019. The Veterans Precision Oncology Data Commons: transforming VA data into a national resource for research in precision oncology. Semin Oncol 46(4\u20135):314\u2013320, PMID: , 10.1053/j.seminoncol.2019.09.002.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jensen MA, Ferretti V, Grossman RL, Staudt LM. 2017. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130(4):453\u2013459, PMID: , 10.1182/blood-2017-03-735654.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Grossman R, Abel B, Angiuoli S, Barrett J, Bassett D, Bramlett K, et al. . 2017. Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium. Clin Pharmacol Ther 101(5):589\u2013592, PMID: , 10.1002/cpt.666.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Heacock ML, Amolegbe SM, Skalla LA, Trottier BA, Carlin DJ, Henry HF, et al. . 2020. Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research. Rev Environ Health 35(2):111\u2013122, PMID: , 10.1515/reveh-2019-0089.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Heacock ML, Lopez AR, Amolegbe SM, Carlin DJ, Henry HF, Trottier BA, et al. . 2022. Enhancing data integration, interoperability, and reuse to address complex and emerging environmental health problems. Environ Sci Technol 56(12):7544\u20137552, PMID: , 10.1021/acs.est.1c08383.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Musen MA. 2022. Without appropriate metadata, data-sharing mandates are pointless. Nature 609(7926):222, PMID: , 10.1038/d41586-022-02820-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Nigam R, Munzenmaier DH, Worthey EA, Dwinell MR, Shimoyama M, Jacob HJ. 2013. Rat strain ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD. J Biomed Semantics 4(1):36, PMID: , 10.1186/2041-1480-4-36.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Percie Du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M, et al. . 2020. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. BMC Vet Res 16(1):242, PMID: , 10.1186/s12917-020-02451-y.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Holmgren SD, Boyles RR, Cronk RD, Duncan CG, Kwok RK, Lunn RM, et al. . 2021. Catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language. Int J Environ Res Public Health 18(17):8985, PMID: , 10.3390/ijerph18178985.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Thomas RS, Clewell HJ 3rd, Allen BC, Wesselkamper SC, Wang NC, Lambert JC, et al. . 2011. Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment. Toxicol Sci 120(1):194\u2013205, PMID: , 10.1093/toxsci/kfq355.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sai L, Yu G, Bo C, Zhang Y, Du Z, Li C, et al. . 2019. Profiling long non-coding RNA changes in silica-induced pulmonary fibrosis in rat. Toxicol Lett 310:7\u201313, PMID: , 10.1016/j.toxlet.2019.04.003.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ojha S, Thompson PT, Powell CD, Moseley HNB, Pennell KG. 2022. A FAIR approach for detecting and sharing PFAS hot-spot areas and water systems. ChemRxiv. Preprint posted online July 25, 2022. 10.26434/chemrxiv-2022-bt3f6.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Rocca-Serra P, Brandizi M, Maguire E, Sklyar N, Taylor C, Begley K, et al. . 2010. ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 26(18):2354\u20132356, PMID: , 10.1093/bioinformatics/btq415.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "M\u00fchlhaus T, Brillhaus D, Tsch\u00f6pe M, Maus O, Gr\u00fcning B, Garth C, et al. 2021. DataPLANT\u2013Tools and Services to structure the Data Jungle for fundamental plant researchers. In: E-Science-Tage 2021: Share Your Research Data. Heuveline V, Bisheh N, eds. Heidelberg, Germany: heiBOOKS, 132\u2013145.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. . 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018, PMID: , 10.1038/sdata.2016.18.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell CD, Moseley HNB. 2022. The metabolomics workbench file status website: a metadata repository promoting FAIR principles of metabolomics data. bioRxiv. Preprint posted online March 7, 2022. 10.1101/2022.03.04.483070.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell CD, Moseley HNB. 2021. The Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11(3):, PMID: , 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "FAIRsharing.org. 2021. Tox Biology Checklist (TBC). https://fairsharing.org/229 [accessed 19 June 2023].", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, et al. . 2021. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 125:105020, PMID: , 10.1016/j.yrtph.2021.105020.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/533452a", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.17226/25116", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", - 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Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it's important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.", - "authors": [ - { - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.", - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Computer Science (Data Science Program), University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.", - "firstname": "Christian D", - "initials": "CD", - "lastname": "Powell" - }, - { - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY, United States of America.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, United States of America.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States of America.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States of America.\nCenter for Clinical and Translational Science, University of Kentucky, Lexington, KY, United States of America.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": "Copyright: \u00a9 2022 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", - "doi": "https://doi.org/10.1371/journal.pone.0277834", - "grants": [ - "P42 ES007380" - ], - "journal": "PloS one", - "keywords": [], - "methods": null, - "publication_date": { - "day": 19, - "month": 11, - "year": 2022 - }, - "pubmed_id": "36399468", - "queried_sources": [ - "PubMed", - "ORCID", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Consolidated Appropriations Act of 2008, H.R. 2764, Editor. 2008: Congressional Record.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Roberts R.J., PubMed Central: The GenBank of the published literature. Proc Natl Acad Sci U S A, 2001. 98(2): p. 381\u20132. doi: 10.1073/pnas.98.2.381", - "doi": "https://doi.org/10.1073/pnas.98.2.381", - "pubmed_id": null, - "title": "PubMed Central: The GenBank of the published literature" - }, - { - "PMCID": null, - "citation": "Rosenzweig M., et al.., National Institutes of Health public access policy and the University of Michigan Libraries\u2019 role in assisting with depositing to PubMed Central. Journal of the Medical Library Association: JMLA, 2011. 99(1): p. 97.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dylla F., CHORUS\u2013A solution for public access. Information services & use, 2014. 34(3\u20134): p. 195\u2013199.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Consolidated Appropriations Act, 2014, H.R. 3547, Editor. 2013: Congressional Record.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kimbrough J.L. and Gasaway L.N., Publication of government-funded research, open access, and the public interest. Vand. J. Ent. & Tech. L., 2015. 18: p. 267.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lappen H. and Creamer A.T., Complying with the NSF\u2019s New Public Access Policy and Depositing a Manuscript in NSF-PAR. 2016.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Haak L.L., et al.., ORCID: a system to uniquely identify researchers. Learned publishing, 2012. 25(4): p. 259\u2013264.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jacs\u00f3 P., Google Scholar: the pros and the cons. Online information review, 2005.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lammey R., CrossRef text and data mining services. Insights, 2015. 28(2).", - "doi": null, - "pubmed_id": null, - "title": "CrossRef text and data mining services" - }, - { - "PMCID": null, - "citation": null, - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": null, - "doi": null, - "pubmed_id": null, - "title": null - } - ], - "results": null, - "title": "Academic Tracker: Software for tracking and reporting publications associated with authors and grants." - }, - "https://doi.org/https://doi.org/10.3390/metabo12060515": { - "PMCID": "PMC9228344", - "abstract": "We present a novel, scan-centric method for characterizing peaks from direct injection multi-scan Fourier transform mass spectra of complex samples that utilizes frequency values derived directly from the spacing of raw ", - "authors": [ - { - "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.\nDepartment of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA.\nResource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA.", - "firstname": "Robert M", - "initials": "RM", - "lastname": "Flight" - }, - { - "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.\nDepartment of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA.\nResource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA.", - "firstname": "Joshua M", - "initials": "JM", - "lastname": "Mitchell" - }, - { - "affiliation": "Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.\nDepartment of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA.\nResource Center for Stable Isotope Resolved Metabolomics, University of Kentucky, Lexington, KY 40536, USA.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY 40536, USA.\nDepartment of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY 40536, USA.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": null, - "doi": "https://doi.org/10.3390/metabo12060515", - "grants": [ - "2020026", - "1P01CA163223-01A1", - "1U24DK097215-01A1", - "P01 CA163223", - "P30 CA177558", - "P30 CA177558", - "U24 DK097215", - "1419282" - ], - "journal": "Metabolites", - "keywords": [ - "Fellgett\u2019s advantage", - "Fourier transform mass spectrometry", - "frequency spectrum", - "interferograms", - "orbitrap", - "scan-centric peak characterization" - ], - "methods": null, - "publication_date": { - "day": 24, - "month": 6, - "year": 2022 - }, - "pubmed_id": "35736448", - "queried_sources": [ - "PubMed", - "ORCID", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Higashi R.M., Fan T.W.-M., Lorkiewicz P.K., Moseley H.N.B., Lane A.N. Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS. In: Raftery D., editor. Mass Spectrometry in Metabolomics: Methods and Protocols. Volume 1198. Humana Press; New York, NY, USA: 2014. pp. 147\u2013167.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinform. 2010;11:139. doi: 10.1186/1471-2105-11-139.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Carreer W.J., Flight R.M., Moseley H.N.B. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets. Metabolites. 2013;3:853\u2013866. doi: 10.3390/metabo3040853.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wang Y., Parsons L.R., Su X. AccuCor2: Isotope natural abundance correction for dual-isotope tracer experiments. Lab. Investig. 2021;101:1403\u20131410. doi: 10.1038/s41374-021-00631-4.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kind T., Fiehn O. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinform. 2006;7:234. doi: 10.1186/1471-2105-7-234.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra. Anal. Chem. 2019;91:8933\u20138940. doi: 10.1021/acs.analchem.9b00748.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Eyles S.J., Kaltashov I.A. Methods to study protein dynamics and folding by mass spectrometry. Methods. 2004;34:88\u201399. doi: 10.1016/j.ymeth.2004.03.015.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dettmer K., Aronov P.A., Hammock B.D. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 2007;26:51\u201378. doi: 10.1002/mas.20108.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Yang Y., Fan T.W.-M., Lane A.N., Higashi R.M. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM) Anal. Chim. Acta. 2017;976:63\u201373. doi: 10.1016/j.aca.2017.04.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creek D.J., Chokkathukalam A., Jankevics A., Burgess K.E.V., Breitling R., Barrett M.P. Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation. Anal. Chem. 2012;84:8442\u20138447. doi: 10.1021/ac3018795.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hiller K., Metallo C.M., Kelleher J.K., Stephanopoulos G. Nontargeted Elucidation of Metabolic Pathways Using Stable-Isotope Tracers and Mass Spectrometry. Anal. Chem. 2010;82:6621\u20136628. doi: 10.1021/ac1011574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fan T.W.-M., Lorkiewicz P.K., Sellers K., Moseley H., Higashi R.M., Lane A.N. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 2012;133:366\u2013391. doi: 10.1016/j.pharmthera.2011.12.007.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Sellers K., Fox M.P., Bousamra M., Slone S.P., Higashi R.M., Miller D.M., Wang Y., Yan J., Yuneva M.O., Deshpande R., et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Investig. 2015;125:687\u2013698. doi: 10.1172/JCI72873.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Verdegem D., Moseley H.N.B., Vermaelen W., Sanchez A.A., Ghesqui\u00e8re B. MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites. Metabolomics. 2017;13:123. doi: 10.1007/s11306-017-1250-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N.B. Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues. BMC Bioinform. 2019;20:254. doi: 10.1186/s12859-019-3096-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jin H., Moseley H.N. Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues. Metabolites. 2020;10:118. doi: 10.3390/metabo10030118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Wang Q.J., Higashi R.M., Fan T.W.-M., Lane A.N., Moseley H.N.B. New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis. Metabolomics. 2018;14:125. doi: 10.1007/s11306-018-1426-9.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N. Deriving Lipid Classification Based on Molecular Formulas. Metabolites. 2020;10:122. doi: 10.3390/metabo10030122.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mitchell J.M., Flight R.M., Moseley H.N.B. Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue. Metabolites. 2021;11:740. doi: 10.3390/metabo11110740.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Moseley H.N. Error Analysis and Propagation In Metabolomics Data Analysis. Comput. Struct. Biotechnol. J. 2013;4:e201301006. doi: 10.5936/csbj.201301006.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Cleveland W.S., Grosse E., Shyu W.M. Local regression models. In: Chambers J.M., Hastie T.J., editors. Statistical Models in S. Wadsworth & Brooks/Cole; Pacific Grove, CA, USA: 1992.", - "doi": null, - "pubmed_id": null, - "title": "Local regression models" - }, - { - "PMCID": null, - "citation": "Sampford M.R. The Truncated Negative Binomial Distribution. Biometrika. 1955;42:58. doi: 10.1093/biomet/42.1-2.58.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ledford E.B., Rempel D.L., Gross M.L. Space charge effects in Fourier transform mass spectrometry. II. Mass calibration. Anal. Chem. 1984;56:2744\u20132748. doi: 10.1021/ac00278a027.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lawrence M., Huber W., Pag\u00e8s H., Aboyoun P., Carlson M., Gentleman R., Morgan M., Carey V.J. Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol. 2013;9:e1003118. doi: 10.1371/journal.pcbi.1003118.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Borchers H.W. Pracma: Practical Numerical Math Functions. 2021. [(accessed on 7 December 2021)]. Available online: https://CRAN.R-project.org/package=pracma.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Bhatt P.S., Moseley H.N. Information-Content-Informed Kendall-Tau Correlation: Utilizing Missing Values. bioRvix. 2022 doi: 10.1101/2022.02.24.481854. preprint .", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Truncated Normal Distribution. Wikipedia. 2022. [(accessed on 16 March 2022)]. Available online: https://en.wikipedia.org/w/index.php?title=Truncated_normal_distribution&oldid=1074943875.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Burkardt J. The Truncated Normal Distribution. [(accessed on 22 March 2022)]. Available online: https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gentleman R., Carey V.J., Huber W., Hahne F. Genefilter: Methods for Filtering Genes from High-Throughput Experiments. [(accessed on 26 October 2021)]. Available online: https://bioconductor.org/packages/3.14/bioc/html/genefilter.html.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "R Core Team . R: A Language and Environment for Statistical Computing. R Core Team; Vienna, Austria: 2021. [(accessed on 20 May 2021)]. Available online: https://www.R-project.org/", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Van Rossum G., Drake F.L. Python 3 Reference Manual. CreateSpace; Scotts Valley, CA, USA: 2009.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Landau W.M. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. J. Open Source Softw. 2021;6:2959. doi: 10.21105/joss.02959.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ushey K. Renv: Project Environments. 2022. [(accessed on 28 February 2022)]. Available online: https://CRAN.R-project.org/package=renv.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H. Ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016. [(accessed on 25 June 2021)]. Available online: https://ggplot2.tidyverse.org.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Patchwork: The Composer of Plots. 2020. [(accessed on 17 December 2020)]. Available online: https://CRAN.R-project.org/package=patchwork.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gu Z., Eils R., Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847\u20132849. doi: 10.1093/bioinformatics/btw313.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wilke C.O. Ggridges: Ridgeline Plots in \u201cggplot2\u201d. 2021. [(accessed on 8 January 2021)]. Available online: https://CRAN.R-project.org/package=ggridges.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pedersen T.L. Ggforce: Accelerating \u201cggplot2\u201d. 2021. [(accessed on 5 March 2021)]. Available online: https://CRAN.R-project.org/package=ggforce.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gatto L., Gibb S., Rainer J. MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. J. Proteome Res. 2021;20:1063\u20131069. doi: 10.1021/acs.jproteome.0c00313.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gatto L., Lilley K. MSnbase\u2014An R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. 2012;28:288\u2013289. doi: 10.1093/bioinformatics/btr645.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N. Visualization Quality Control: Development of Visualization Methods for Quality Control. 2021. [(accessed on 3 December 2021)]. Available online: https://moseleybioinformaticslab.github.io/visualizationQualityControl.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H., Fran\u00e7ois R., Henry L., M\u00fcller K. Dplyr: A Grammar of Data Manipulation. 2022. [(accessed on 8 February 2022)]. Available online: https://CRAN.R-project.org/package=dplyr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Wickham H., Girlich M. Tidyr: Tidy Messy Data. 2022. [(accessed on 1 February 2022)]. Available online: https://CRAN.R-project.org/package=tidyr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Vaughan D., Dancho M. Furrr: Apply Mapping Functions in Parallel Using Futures. 2021. [(accessed on 30 June 2021)]. Available online: https://CRAN.R-project.org/package=furrr.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Allaire J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. 2021. [(accessed on 1 April 2022)]. Available online: https://github.com/rstudio/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Xie Y., Allaire J.J., Grolemund G. R Markdown: The Definitive Guide. Chapman and Hall/CRC; Boca Raton, FL, USA: 2018. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Xie Y., Dervieux C., Riederer E. R Markdown Cookbook. Chapman and Hall/CRC; Boca Raton, FL, USA: 2020. [(accessed on 1 April 2022)]. Available online: https://bookdown.org/yihui/rmarkdown-cookbook.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Mitchell J.M., Moseley H.N.B. Moseley Bioinformatics Lab/Manuscript.Peak Characterization. 2022. [(accessed on 1 April 2022)]. Available online: https://zenodo.org/record/6453346#.YpiialRBxPY.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Flight R.M., Moseley H.N.B. Moseley Bioinformatics Lab/FTMS.Peak Characterization: V0.1.102. Zenodo. 2022. [(accessed on 1 April 2022)]. 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Therefore, we used liquid chromatography-mass spectroscopy (LC-MS) to determine the hepatic lipid composition of obese mice with NAFLD treated with bilirubin nanoparticles or vehicle control. We placed the mice on a high-fat diet (HFD) for 24 weeks and then treated them with bilirubin nanoparticles or vehicle control for 4 weeks while maintaining the HFD. Bilirubin nanoparticles suppressed hepatic fat content overall. After analyzing the lipidomics data, we determined that bilirubin inhibited the accumulation of ceramides in the liver. The bilirubin nanoparticles significantly lowered the hepatic expression of two essential enzymes that regulate ceramide production, ", - "authors": [ - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky, 760 Press Avenue, Healthy Kentucky Research Building, Lexington, KY 40508, USA.", - "firstname": "Zachary A", - "initials": "ZA", - "lastname": "Kipp" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky, 760 Press Avenue, Healthy Kentucky Research Building, Lexington, KY 40508, USA.", - "firstname": "Genesee J", - "initials": "GJ", - "lastname": "Martinez" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky, 760 Press Avenue, Healthy Kentucky Research Building, Lexington, KY 40508, USA.", - "firstname": "Evelyn A", - "initials": "EA", - "lastname": "Bates" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky, 760 Press Avenue, Healthy Kentucky Research Building, Lexington, KY 40508, USA.", - "firstname": "Agil B", - "initials": "AB", - "lastname": "Maharramov" - }, - { - "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40508, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY 40508, USA.", - "firstname": "Robert M", - "initials": "RM", - "lastname": "Flight" - }, - { - "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40508, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY 40508, USA.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY 40508, USA.\nCenter for Clinical and Translational Sciences, University of Kentucky, Lexington, KY 40508, USA.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - }, - { - "affiliation": "Department of Pharmacology and Toxicology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.", - "firstname": "Andrew J", - "initials": "AJ", - "lastname": "Morris" - }, - { - "affiliation": "Department of Physiology & Biophysics, Cardiorenal, and Metabolic Diseases Research Center, University of Mississippi Medical Center, Jackson, MS 39216, USA.", - "firstname": "David E", - "initials": "DE", - "lastname": "Stec" - }, - { - "affiliation": "Department of Pharmacology and Nutritional Sciences, University of Kentucky, 760 Press Avenue, Healthy Kentucky Research Building, Lexington, KY 40508, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY 40508, USA.\nBarnstable Brown Diabetes Center, University of Kentucky, Lexington, KY 40508, USA.", - "firstname": "Terry D", - "initials": "TD", - "lastname": "Hinds" - } - ], - "conclusions": null, - "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13020215", - "grants": [ - "P30 GM127211", - "P20 GM104357", - "R01DK121797", - "P20GM104357", - "R01DK126884" - ], - "journal": "Metabolites", - "keywords": [ - "Blvra", - "HO-1", - "NAFLD", - "bilirubin", - "ceramides", - "heme oxygenase", - "hepatic steatosis", - "lipidomics", - "lipids", - "obese" - ], - "methods": null, - "publication_date": { - "day": 26, - "month": 2, - "year": 2023 - }, - "pubmed_id": "36837834", - "queried_sources": [ - "PubMed", - "ORCID", - "Google Scholar" - ], - "references": [ - { - "PMCID": null, - "citation": "Riazi K., Azhari H., Charette J.H., Underwood F.E., King J.A., Afshar E.E., Swain M.G., Congly S.E., Kaplan G.G., Shaheen A.A. The prevalence and incidence of NAFLD worldwide: A systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 2022;7:851\u2013861. doi: 10.1016/S2468-1253(22)00165-0.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Badmus O.O., Hillhouse S.A., Anderson C.D., Hinds T.D., Stec D.E. Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): Functional analysis of lipid metabolism pathways. Clin. Sci. 2022;136:1347\u20131366. doi: 10.1042/CS20220572.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Brunt E.M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 2010;7:195\u2013203. doi: 10.1038/nrgastro.2010.21.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Targher G., Corey K.E., Byrne C.D., Roden M. The complex link between NAFLD and type 2 diabetes mellitus\u2014Mechanisms and treatments. Nat. Rev. Gastroenterol. Hepatol. 2021;18:599\u2013612. doi: 10.1038/s41575-021-00448-y.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kasper P., Martin A., Lang S., Kutting F., Goeser T., Demir M., Steffen H.M. NAFLD and cardiovascular diseases: A clinical review. Clin. Res. Cardiol. 2021;110:921\u2013937. doi: 10.1007/s00392-020-01709-7.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creeden J.F., Gordon D.M., Stec D.E., Hinds T.D., Jr. Bilirubin as a metabolic hormone: The physiological relevance of low levels. Am. J. Physiol. Endocrinol. Metab. 2021;320:E191\u2013E207. doi: 10.1152/ajpendo.00405.2020.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Stec D.E., John K., Trabbic C.J., Luniwal A., Hankins M.W., Baum J., Hinds T.D., Jr. Bilirubin Binding to PPARalpha Inhibits Lipid Accumulation. PLoS ONE. 2016;11:e0153427. doi: 10.1371/journal.pone.0153427.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gordon D.M., Hong S.H., Kipp Z.A., Hinds T.D., Jr. Identification of Binding Regions of Bilirubin in the Ligand-Binding Pocket of the Peroxisome Proliferator-Activated Receptor-A (PPARalpha) Molecules. 2021;26:2975. doi: 10.3390/molecules26102975.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gordon D.M., Blomquist T.M., Miruzzi S.A., McCullumsmith R., Stec D.E., Hinds T.D., Jr. RNA sequencing in human HepG2 hepatocytes reveals PPAR-alpha mediates transcriptome responsiveness of bilirubin. Physiol. Genom. 2019;51:234\u2013240. doi: 10.1152/physiolgenomics.00028.2019.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gordon D.M., Neifer K.L., Hamoud A.A., Hawk C.F., Nestor-Kalinoski A.L., Miruzzi S.A., Morran M.P., Adeosun S.O., Sarver J.G., Erhardt P.W., et al. Bilirubin remodels murine white adipose tissue by reshaping mitochondrial activity and the coregulator profile of peroxisome proliferator-activated receptor alpha. J. Biol. Chem. 2020;295:9804\u20139822. doi: 10.1074/jbc.RA120.013700.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Stec D.F., Donald M.C., Stec D.E. Bilirubin Nanoparticles Reduce Diet-Induced Hepatic Steatosis, Improve Fat Utilization, and Increase Plasma beta-Hydroxybutyrate. Front. Pharmacol. 2020;11:594574. doi: 10.3389/fphar.2020.594574.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pagadala M., Kasumov T., McCullough A.J., Zein N.N., Kirwan J.P. Role of ceramides in nonalcoholic fatty liver disease. Trends Endocrinol. Metab. 2012;23:365\u2013371. doi: 10.1016/j.tem.2012.04.005.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Levy M., Futerman A.H. Mammalian ceramide synthases. IUBMB Life. 2010;62:347\u2013356. doi: 10.1002/iub.319.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kitatani K., Idkowiak-Baldys J., Hannun Y.A. The sphingolipid salvage pathway in ceramide metabolism and signaling. Cell. Signal. 2008;20:1010\u20131018. doi: 10.1016/j.cellsig.2007.12.006.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Poss A.M., Summers S.A. Too Much of a Good Thing? An Evolutionary Theory to Explain the Role of Ceramides in NAFLD. Front. Endocrinol. 2020;11:505. doi: 10.3389/fendo.2020.00505.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Jiang M., Li C., Liu Q., Wang A., Lei M. Inhibiting Ceramide Synthesis Attenuates Hepatic Steatosis and Fibrosis in Rats With Non-alcoholic Fatty Liver Disease. Front. Endocrinol. 2019;10:665. doi: 10.3389/fendo.2019.00665.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds T.D., Jr., Burns K.A., Hosick P.A., McBeth L., Nestor-Kalinoski A., Drummond H.A., AlAmodi A.A., Hankins M.W., Vanden Heuvel J.P., Stec D.E. Biliverdin reductase A attenuates hepatic steatosis by inhibition of glycogen synthase kinase (GSK) 3beta phosphorylation of serine 73 of peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25179\u201325191. doi: 10.1074/jbc.M116.731703.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Creeden J.F., Kipp Z.A., Xu M., Flight R.M., Moseley H.N.B., Martinez G.J., Lee W.H., Alganem K., Imami A.S., McMullen M.R., et al. Hepatic Kinome Atlas: An In-Depth Identification of Kinase Pathways in Liver Fibrosis of Humans and Rodents. Hepatology. 2022;76:1376\u20131388. doi: 10.1002/hep.32467.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds T.D., Jr., Creeden J.F., Gordon D.M., Spegele A.C., Britton S.L., Koch L.G., Stec D.E. Rats Genetically Selected for High Aerobic Exercise Capacity Have Elevated Plasma Bilirubin by Upregulation of Hepatic Biliverdin Reductase-A (BVRA) and Suppression of UGT1A1. Antioxidants. 2020;9:889. doi: 10.3390/antiox9090889.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Stec D.E., Gordon D.M., Hipp J.A., Hong S., Mitchell Z.L., Franco N.R., Robison J.W., Anderson C.D., Stec D.F., Hinds T.D., Jr. The loss of hepatic PPARalpha promotes inflammation and serum hyperlipidemia in diet-induced obesity. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2019;317:R733\u2013R745. doi: 10.1152/ajpregu.00153.2019.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds T.D., Jr., Hosick P.A., Hankins M.W., Nestor-Kalinoski A., Stec D.E. Mice with hyperbilirubinemia due to Gilbert\u2019s Syndrome polymorphism are resistant to hepatic steatosis by decreased serine 73 phosphorylation of PPARalpha. Am. J. Physiol. Endocrinol. Metab. 2017;312:E244\u2013E252. doi: 10.1152/ajpendo.00396.2016.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lee Y., Kim H., Kang S., Lee J., Park J., Jon S. Bilirubin Nanoparticles as a Nanomedicine for Anti-inflammation Therapy. Angew. Chem. Int. Ed. Engl. 2016;55:7460\u20137463. doi: 10.1002/anie.201602525.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kim D.E., Lee Y., Kim M., Lee S., Jon S., Lee S.H. Bilirubin nanoparticles ameliorate allergic lung inflammation in a mouse model of asthma. Biomaterials. 2017;140:37\u201344. doi: 10.1016/j.biomaterials.2017.06.014.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Mueller P.A., Yang L., Ubele M., Mao G., Brandon J., Vandra J., Nichols T.C., Escalante-Alcalde D., Morris A.J., Smyth S.S. Coronary Artery Disease Risk-Associated Plpp3 Gene and Its Product Lipid Phosphate Phosphatase 3 Regulate Experimental Atherosclerosis. Arter. Thromb. Vasc. Biol. 2019;39:2261\u20132272. doi: 10.1161/ATVBAHA.119.313056.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kraemer M.P., Mao G., Hammill C., Yan B., Li Y., Onono F., Smyth S.S., Morris A.J. Effects of diet and hyperlipidemia on levels and distribution of circulating lysophosphatidic acid. J. Lipid Res. 2019;60:1818\u20131828. doi: 10.1194/jlr.M093096.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Khan M.J., Codreanu S.G., Goyal S., Wages P.A., Gorti S.K.K., Pearson M.J., Uribe I., Sherrod S.D., McLean J.A., Porter N.A., et al. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma. Rapid Commun. Mass Spectrom. 2020;34:e8911. doi: 10.1002/rcm.8911.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Lin W.J., Shen P.C., Liu H.C., Cho Y.C., Hsu M.K., Lin I.C., Chen F.H., Yang J.C., Ma W.L., Cheng W.C. LipidSig: A web-based tool for lipidomic data analysis. Nucleic Acids Res. 2021;49:W336\u2013W345. doi: 10.1093/nar/gkab419.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gaud C., Sousa B.C., Nguyen A., Fedorova M., Ni Z., O\u2019Donnell V.B., Wakelam M.J.O., Andrews S., Lopez-Clavijo A.F. BioPAN: A web-based tool to explore mammalian lipidome metabolic pathways on LIPID MAPS. F1000Res. 2021;10:4. doi: 10.12688/f1000research.28022.1.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Marino J.S., Stechschulte L.A., Stec D.E., Nestor-Kalinoski A., Coleman S., Hinds T.D., Jr. Glucocorticoid receptor beta induces hepatic steatosis by augmenting inflammation and inhibition of the peroxisome proliferator-activated receptor (PPAR) alpha. J. Biol. Chem. 2016;291:25776\u201325788. doi: 10.1074/jbc.M116.752311.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds T.D., Jr., Kipp Z.A., Xu M., Yiannikouris F.B., Morris A.J., Stec D.F., Wahli W., Stec D.E. Adipose-Specific PPARalpha Knockout Mice Have Increased Lipogenesis by PASK-SREBP1 Signaling and a Polarity Shift to Inflammatory Macrophages in White Adipose Tissue. Cells. 2021;11:4. doi: 10.3390/cells11010004.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ruangsiriluk W., Grosskurth S.E., Ziemek D., Kuhn M., des Etages S.G., Francone O.L. Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression. J. Lipid. Res. 2012;53:1459\u20131471. doi: 10.1194/jlr.M020941.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Bektas M., Allende M.L., Lee B.G., Chen W., Amar M.J., Remaley A.T., Saba J.D., Proia R.L. Sphingosine 1-phosphate lyase deficiency disrupts lipid homeostasis in liver. J. Biol. Chem. 2010;285:10880\u201310889. doi: 10.1074/jbc.M109.081489.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Kipp Z.A., Xu M., Bates E.A., Lee W.-H., Kern P.A., Hinds T.D. Bilirubin Levels Are Negatively Correlated with Adiposity in Obese Men and Women, and Its Catabolized Product, Urobilin, Is Positively Associated with Insulin Resistance. Antioxidants. 2023;12:170. doi: 10.3390/antiox12010170.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin Safeguards Cardiorenal and Metabolic Diseases: A Protective Role in Health. Curr. Hypertens. Rep. 2019;21:87. doi: 10.1007/s11906-019-0994-z.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds T.D., Jr., Stec D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension. 2018;72:788\u2013795. doi: 10.1161/HYPERTENSIONAHA.118.11130.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Weaver L., Hamoud A.R., Stec D.E., Hinds T.D., Jr. Biliverdin reductase and bilirubin in hepatic disease. Am. J. Physiol. Gastrointest Liver Physiol. 2018;314:G668\u2013G676. doi: 10.1152/ajpgi.00026.2018.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hamoud A.R., Weaver L., Stec D.E., Hinds T.D., Jr. Bilirubin in the Liver-Gut Signaling Axis. Trends Endocrinol Metab. 2018;29:140\u2013150. doi: 10.1016/j.tem.2018.01.002.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Chen W., Tumanov S., Fazakerley D.J., Cantley J., James D.E., Dunn L.L., Shaik T., Suarna C., Stocker R. Bilirubin deficiency renders mice susceptible to hepatic steatosis in the absence of insulin resistance. Redox Biol. 2021;47:102152. doi: 10.1016/j.redox.2021.102152.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Stec D.E., Hinds T.D., Jr. Natural Product Heme Oxygenase Inducers as Treatment for Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020;21:9493. doi: 10.3390/ijms21249493.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Hinds T.D., Jr., Adeosun S.O., Alamodi A.A., Stec D.E. Does bilirubin prevent hepatic steatosis through activation of the PPARalpha nuclear receptor? Med. Hypotheses. 2016;95:54\u201357. doi: 10.1016/j.mehy.2016.08.013.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Takei R., Inoue T., Sonoda N., Kohjima M., Okamoto M., Sakamoto R., Inoguchi T., Ogawa Y. Bilirubin reduces visceral obesity and insulin resistance by suppression of inflammatory cytokines. PLoS ONE. 2019;14:e0223302. doi: 10.1371/journal.pone.0223302.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Galadari S., Rahman A., Pallichankandy S., Galadari A., Thayyullathil F. Role of ceramide in diabetes mellitus: Evidence and mechanisms. Lipids Health Dis. 2013;12:98. doi: 10.1186/1476-511X-12-98.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell D.J., Hajduch E., Kular G., Hundal H.S. Ceramide disables 3-phosphoinositide binding to the pleckstrin homology domain of protein kinase B (PKB)/Akt by a PKCzeta-dependent mechanism. Mol. Cell Biol. 2003;23:7794\u20137808. doi: 10.1128/MCB.23.21.7794-7808.2003.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Arendt B.M., Ma D.W., Simons B., Noureldin S.A., Therapondos G., Guindi M., Sherman M., Allard J.P. Nonalcoholic fatty liver disease is associated with lower hepatic and erythrocyte ratios of phosphatidylcholine to phosphatidylethanolamine. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Et Metab. 2013;38:334\u2013340. doi: 10.1139/apnm-2012-0261.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Trentzsch M., Nyamugenda E., Miles T.K., Griffin H., Russell S., Koss B., Cooney K.A., Phelan K.D., Tackett A.J., Iyer S., et al. Delivery of phosphatidylethanolamine blunts stress in hepatoma cells exposed to elevated palmitate by targeting the endoplasmic reticulum. Cell Death Discov. 2020;6:8. doi: 10.1038/s41420-020-0241-z.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Dong H., Huang H., Yun X., Kim D.S., Yue Y., Wu H., Sutter A., Chavin K.D., Otterbein L.E., Adams D.B., et al. Bilirubin increases insulin sensitivity in leptin-receptor deficient and diet-induced obese mice through suppression of ER stress and chronic inflammation. Endocrinology. 2014;155:818\u2013828. doi: 10.1210/en.2013-1667.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fujii M., Inoguchi T., Sasaki S., Maeda Y., Zheng J., Kobayashi K., Takayanagi R. Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase. Kidney Int. 2010;78:905\u2013919. doi: 10.1038/ki.2010.265.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Stocker R., Yamamoto Y., McDonagh A.F., Glazer A.N., Ames B.N. Bilirubin is an antioxidant of possible physiological importance. Science. 1987;235:1043\u20131046. doi: 10.1126/science.3029864.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gordon D.M., Adeosun S.O., Ngwudike S.I., Anderson C.D., Hall J.E., Hinds T.D., Jr., Stec D.E. CRISPR Cas9-mediated deletion of biliverdin reductase A (BVRA) in mouse liver cells induces oxidative stress and lipid accumulation. Arch. Biochem. Biophys. 2019;672:108072. doi: 10.1016/j.abb.2019.108072.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Adeosun S.O., Gordon D.M., Weeks M.F., Moore K.H., Hall J.E., Hinds T.D., Stec D.E. Loss of biliverdin reductase-A (BVRA) promotes lipid accumulation and lipotoxicity in mouse proximal tubule cells. Am. J. Physiol. Renal. Physiol. 2018;315:F323\u2013F331. doi: 10.1152/ajprenal.00495.2017.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Thomas D.T., DelCimmuto N.R., Flack K.D., Stec D.E., Hinds T.D., Jr. Reactive Oxygen Species (ROS) and Antioxidants as Immunomodulators in Exercise: Implications for Heme Oxygenase and Bilirubin. Antioxidants. 2022;11:179. doi: 10.3390/antiox11020179.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Chaurasia B., Tippetts T.S., Mayoral Monibas R., Liu J., Li Y., Wang L., Wilkerson J.L., Sweeney C.R., Pereira R.F., Sumida D.H., et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365:386\u2013392. doi: 10.1126/science.aav3722.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Albi E., Alessenko A., Grosch S. Sphingolipids in Inflammation. Mediat. Inflamm. 2018;2018:7464702. doi: 10.1155/2018/7464702.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Ai W., Bae S., Ke Q., Su S., Li R., Chen Y., Yoo D., Lee E., Jon S., Kang P.M. Bilirubin Nanoparticles Protect Against Cardiac Ischemia/Reperfusion Injury in Mice. J. Am. Heart Assoc. 2021;10:e021212. doi: 10.1161/JAHA.121.021212.", - "doi": null, - "pubmed_id": null, - "title": null - } - ], - "results": null, - "title": "Bilirubin Nanoparticle Treatment in Obese Mice Inhibits Hepatic Ceramide Production and Remodels Liver Fat Content." - }, - "https://doi.org/https://doi.org/10.3390/metabo13070842": { - "PMCID": "PMC10386444", - "abstract": "In recent years, the FAIR guiding principles and the broader concept of open science has grown in importance in academic research, especially as funding entities have aggressively promoted public sharing of research products. Key to public research sharing is deposition of datasets into online data repositories, but it can be a chore to transform messy unstructured data into the forms required by these repositories. To help generate Metabolomics Workbench depositions, we have developed the MESSES (Metadata from Experimental SpreadSheets Extraction System) software package, implemented in the Python 3 programming language and supported on Linux, Windows, and Mac operating systems. MESSES helps transform tabular data from multiple sources into a Metabolomics Workbench specific deposition format. The package provides three commands, extract, validate, and convert, that implement a natural data transformation workflow. Moreover, MESSES facilitates richer metadata capture than is typically attempted by manual efforts. The source code and extensive documentation is hosted on GitHub and is also available on the Python Package Index for easy installation.", - "authors": [ - { - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY 40536, USA.", - "firstname": "P Travis", - "initials": "PT", - "lastname": "Thompson" - }, - { - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY 40536, USA.\nDepartment of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA.\nCenter for Clinical and Translational Science, Lexington, KY 40536, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.\nInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY 40536, USA.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - }, - { - "affiliation": "Superfund Research Center, University of Kentucky, Lexington, KY 40536, USA", - "firstname": "P. Travis", - "initials": null, - "lastname": "Thompson" - } - ], - "conclusions": null, - "copyrights": null, - "doi": "https://doi.org/10.3390/metabo13070842", - "grants": [ - "P42 ES007380", - "P42ES007380" - ], - "journal": "Metabolites", - "keywords": [ - "Metabolomics Workbench", - "Python programming language", - "data sharing", - "data transformation", - "dataset deposition", - "metadata capture" - ], - "methods": null, - "publication_date": { - "day": 29, - "month": 7, - "year": 2023 - }, - "pubmed_id": "37512549", - "queried_sources": [ - "PubMed", - "ORCID", - "Google Scholar", - "Crossref" - ], - "references": [ - { - "PMCID": null, - "citation": "Carroll M. National Academies of Sciences, Engineering, and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. The National Academies Press; Washington, DC, USA: 2018.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Vicente-Saez R., Martinez-Fuentes C. Open Science now: A systematic literature review for an integrated definition. J. Bus. Res. 2018;88:428\u2013436. doi: 10.1016/j.jbusres.2017.12.043.", - "doi": "https://doi.org/10.1016/j.jbusres.2017.12.043", - "pubmed_id": null, - "title": "Open Science now: A systematic literature review for an integrated definition" - }, - { - "PMCID": null, - "citation": "Wilkinson M.D., Dumontier M., Aalbersberg I.J., Appleton G., Axton M., Baak A., Blomberg N., Boiten J.-W., da Silva Santos L.B., Bourne P.E. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:160018. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", - "pubmed_id": null, - "title": "The FAIR Guiding Principles for scientific data management and stewardship" - }, - { - "PMCID": null, - "citation": "Sud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K.S. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44:D463\u2013D470. doi: 10.1093/nar/gkv1042.", - "doi": "https://doi.org/10.1093/nar/gkv1042", - "pubmed_id": null, - "title": "Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools" - }, - { - "PMCID": null, - "citation": "Haug K., Cochrane K., Nainala V.C., Williams M., Chang J., Jayaseelan K.V., O\u2019Donovan C. MetaboLights: A resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48:D440\u2013D444. doi: 10.1093/nar/gkz1019.", - "doi": null, - "pubmed_id": null, - "title": "MetaboLights: A resource evolving in response to the needs of its scientific community" - }, - { - "PMCID": null, - "citation": "NOT-OD-21-013. Vol NOT-OD-21-013. NIH Grants & Funding. National Institutes of Health; Bethesda, MD, USA: 2020. Final NIH policy for data management and sharing.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Fiehn O., Robertson D., Griffin J., van der Werf M., Nikolau B., Morrison N., Sumner L.W., Goodacre R., Hardy N.W., Taylor C. The metabolomics standards initiative (MSI) Metabolomics. 2007;3:175\u2013178. doi: 10.1007/s11306-007-0070-6.", - "doi": "https://doi.org/10.1007/s11306-007-0070-6", - "pubmed_id": null, - "title": "The metabolomics standards initiative (MSI)" - }, - { - "PMCID": null, - "citation": "Powell C.D., Moseley H.N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021;11:163. doi: 10.3390/metabo11030163.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell C.D., Moseley H.N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv. 2022 doi: 10.1101/2022.03.04.483070.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Haug K., Salek R.M., Conesa P., Hastings J., de Matos P., Rijnbeek M., Mahendraker T., Williams M., Neumann S., Rocca-Serra P. MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res. 2012;41:D781\u2013D786. doi: 10.1093/nar/gks1004.", - "doi": "https://doi.org/10.1093/nar/gks1004", - "pubmed_id": null, - "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" - }, - { - "PMCID": null, - "citation": "Salek R.M., Haug K., Conesa P., Hastings J., Williams M., Mahendraker T., Maguire E., Gonzalez-Beltran A.N., Rocca-Serra P., Sansone S.-A. The MetaboLights repository: Curation challenges in metabolomics. Database. 2013;2013:bat029. doi: 10.1093/database/bat029.", - "doi": "https://doi.org/10.1093/database/bat029", - "pubmed_id": null, - "title": "The MetaboLights repository: Curation challenges in metabolomics" - }, - { - "PMCID": null, - "citation": "Docopt Python Library for Creating Command-Line Interfaces. [(accessed on 1 January 2023)]. Available online: http://docopt.readthedocs.io/en/latest/", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pezoa F., Reutter J.L., Suarez F., Ugarte M., Vrgo\u010d D. Foundations of JSON schema; Proceedings of the 25th International Conference on World Wide Web; Montreal, QC, Canada. 11\u201315 April 2016; pp. 263\u2013273.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Droettboom M. Understanding JSON Schema. 2014. [(accessed on 1 January 2023)]. Available online: http://spacetelescope.github.io/understanding-jsonschema/UnderstandingJSONSchema.pdf.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Open JS Foundation. 2019. [(accessed on 1 January 2023)]. Available online: https://openjsf.org/", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "McKinney W. Pandas: A foundational Python library for data analysis and statistics. Python High Perform. Sci. Comput. 2011;14:1\u20139.", - "doi": null, - "pubmed_id": null, - "title": "Pandas: A foundational Python library for data analysis and statistics" - }, - { - "PMCID": null, - "citation": "Oliphant T.E. A Guide to NumPy. Volume 1 Trelgol Publishing; Spanish Fork, UT, USA: 2006.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gazoni E., Clark C. openpyxl\u2014A Python Library to Read/Write Excel 2010 xlsx/xlsm Files. 2016. [(accessed on 1 January 2023)]. Available online: http://openpyxl.readthedocs.org/en/default.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Behnel S., Bradshaw R., Citro C., Dalcin L., Seljebotn D.S., Smith K. Cython: The best of both worlds. Comput. Sci. Eng. 2011;13:31\u201339. doi: 10.1109/MCSE.2010.118.", - "doi": "https://doi.org/10.1109/MCSE.2010.118", - "pubmed_id": null, - "title": "Cython: The best of both worlds" - }, - { - "PMCID": null, - "citation": "Smelter A., Moseley H.N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics. 2018;14:64. doi: 10.1007/s11306-018-1356-6.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", - "pubmed_id": null, - "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" - }, - { - "PMCID": null, - "citation": "Hildebrandt G. Metabolomics of Lung Injury after Allogeneic Hematopoietic Cell Transplantation\u2014Colon ICMS. [(accessed on 1 January 2020)]. Available online: https://www.metabolomicsworkbench.org/data/DRCCMetadata.php?Mode=Project&ProjectID=PR000993.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Organisation for Economic Co-Operation Development Draft Advisory Document of the Working Group on Good Laboratory Practice on GLP Data Integrity. [(accessed on 1 January 2023)]. Available online: https://www.oecd.org/env/ehs/testing/DRAFT_OECD_Advisory_Document_on_GLP_Data_Integrity_07_August_2020.pdf.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "(2020). NOT-OD-21-013. Vol NOT-OD-21-013. NIH Grants & Funding, National Institutes of Health.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Powell, C.D., and Moseley, H.N. (2021). The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites, 11.", - "doi": "https://doi.org/10.3390/metabo11030163", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "(2023, January 01). Docopt Python Library for Creating Command-Line Interfaces. Available online: http://docopt.readthedocs.io/en/latest/.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Droettboom, M. (2023, January 01). Understanding JSON Schema. Available online: http://spacetelescope.github.io/understanding-jsonschema/UnderstandingJSONSchema.pdf.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "(2023, January 01). Open JS Foundation. Available online: https://openjsf.org/.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Oliphant, T.E. (2006). A Guide to NumPy, Trelgol Publishing.", - "doi": null, - "pubmed_id": null, - "title": null - }, - { - "PMCID": null, - "citation": "Gazoni, E., and Clark, C. (2023, January 01). openpyxl\u2014A Python Library to Read/Write Excel 2010 xlsx/xlsm Files. Available online: http://openpyxl.readthedocs.org/en/default.", - "doi": null, - "pubmed_id": null, - "title": null - } - ], - "results": null, - "title": "MESSES: Software for Transforming Messy Research Datasets into Clean Submissions to Metabolomics Workbench for Public Sharing." - }, - "https://www.biorxiv.org/content/10.1101/2022.02.24.481854.abstract": { - "PMCID": null, - "abstract": null, - "authors": [ - { - "affiliation": "kentucky", - "author_id": "Hunter Moseley", - "firstname": "Hunter", - "initials": null, - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": null, - "doi": null, - "grants": [], - "journal": null, - "keywords": null, - "methods": null, - "publication_date": { - "day": null, - "month": null, - "year": 2022 - }, - "pubmed_id": null, - "queried_sources": [ - "Google Scholar" - ], - "references": [], - "results": null, - "title": "Information-content-informed kendall-tau correlation: Utilizing missing values" - }, - "https://www.biorxiv.org/content/10.1101/2022.12.08.519680.abstract": { - "PMCID": null, - "abstract": null, - "authors": [ - { - "affiliation": "kentucky", - "author_id": "Hunter Moseley", - "firstname": "Hunter", - "initials": null, - "lastname": "Moseley" - } - ], - "conclusions": null, - "copyrights": null, - "doi": null, - "grants": [], - "journal": null, - "keywords": null, - "methods": null, - "publication_date": { - "day": null, - "month": null, - "year": 2022 - }, - "pubmed_id": null, - "queried_sources": [ - "Google Scholar" - ], - "references": [], - "results": null, - "title": "md_harmonize: a Python package for atom-level harmonization of public metabolic data-bases" - } -} diff --git a/tests/testing_files/publication_dict_truncated.json b/tests/testing_files/publication_dict_truncated.json index 0430159..5d53acc 100644 --- a/tests/testing_files/publication_dict_truncated.json +++ b/tests/testing_files/publication_dict_truncated.json @@ -183,7 +183,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2022 The Authors. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.", - "doi": "https://doi.org/10.1002/hep.32467", + "doi": "10.1002/hep.32467", "grants": [ "R01 MH121102", "R01 AG057598", @@ -572,7 +572,7 @@ ], "conclusions": null, "copyrights": "\u00a9 2023. The Author(s).", - "doi": "https://doi.org/10.1038/s41597-023-02277-x", + "doi": "10.1038/s41597-023-02277-x", "grants": [ "P42 ES007380", "2020026" @@ -603,21 +603,21 @@ { "PMCID": null, "citation": "Da Silva BF, Ahmadireskety A, Aristizabal-Henao JJ, Bowden JA. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 2020;7:101111\u201310111. doi: 10.1016/j.mex.2020.101111.", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom AL, et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS) Sci. Total Envir. 2021;778:146192. doi: 10.1016/j.scitotenv.2021.146192.", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen T, et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 2021;1172:122653. doi: 10.1016/j.jchromb.2021.122653.", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -631,98 +631,98 @@ { "PMCID": null, "citation": "Rogers RD, Reh CM, Breysse P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 2021;31:961\u2013971. doi: 10.1038/s41370-021-00316-6.", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s M, Berger U, Hop H, Gulliksen B, Gabrielsen GW. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 2007;148:360\u2013371. doi: 10.1016/j.envpol.2006.09.021.", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton SE, et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 2021;40:606\u2013630. doi: 10.1002/etc.4890.", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk KH, Darlington R, Benotti M, Deeb R, Hawley E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 2017;204:757\u2013764. doi: 10.1016/j.jenvman.2017.08.016.", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. 10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman MF, Peldszus S, Anderson WB. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 2014;50:318\u2013340. doi: 10.1016/j.watres.2013.10.045.", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva AO, et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 2021;40:631\u2013657. doi: 10.1002/etc.4935.", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen GW, et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 2017;157:87\u201395. doi: 10.1016/j.envres.2017.05.013.", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo JL, Nadal M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 2019;177:108648\u2013108648. doi: 10.1016/j.envres.2019.108648.", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn E, et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 2019;248:101\u2013113. doi: 10.1016/j.envpol.2019.02.018.", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai X, Son Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 2021;751:141622\u2013141622. doi: 10.1016/j.scitotenv.2020.141622.", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li Y, et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 2022;216:118295\u2013118295. doi: 10.1016/j.watres.2022.118295.", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale SE, et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 2017;171:9\u201318. doi: 10.1016/j.chemosphere.2016.12.057.", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber JL, et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 2007;9:530\u2013541. doi: 10.1039/b701417a.", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -736,28 +736,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9 MA, et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 2021;55:5848\u20135856. doi: 10.1021/acs.est.0c07978.", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens L, Norstr\u00f6m K, Viktor T, Cousins AP, Josefsson S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 2015;129:33\u201338. doi: 10.1016/j.chemosphere.2014.03.136.", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson DT, et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 2020;54:15768\u201315777. doi: 10.1021/acs.est.0c04472.", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan J, et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 2021;31:7\u201326. doi: 10.1002/rem.21680.", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -771,42 +771,42 @@ { "PMCID": null, "citation": "Hale SE, Canivet B, Rundberget T, Langberg HA, Allan IJ. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 2021;9:621\u2013629. doi: 10.3389/fenvs.2021.796026.", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu XC, et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 2016;3:344\u2013350. doi: 10.1021/acs.estlett.6b00260.", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha S, et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 2023;19:163\u2013174. doi: 10.1002/ieam.4614.", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert JC, Altman RB. Robust recognition of zinc binding sites in proteins. Protein Sci. 2008;17:54\u201365. doi: 10.1110/ps.073138508.", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 2016;3:1\u20139. doi: 10.1038/sdata.2016.18.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, Zielhuis GA, Bredenoord AL. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 2018;26:931\u2013936. doi: 10.1038/s41431-018-0160-0.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -820,21 +820,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka \u00c1, Szer\u00e9nyi ZM, Sz\u00e9chy A, Kocsis T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 2013;48:126\u2013138. doi: 10.1016/j.jclepro.2012.11.030.", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo JL, Adamson DT. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 2018;236:505\u2013513. doi: 10.1016/j.envpol.2018.01.066.", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja S, Thompson PT, Powell CD, Moselet HNB, Pennell KP. 2022. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare.", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } diff --git a/tests/testing_files/publication_dict_truncated_old.json b/tests/testing_files/publication_dict_truncated_old.json deleted file mode 100644 index bd80653..0000000 --- a/tests/testing_files/publication_dict_truncated_old.json +++ /dev/null @@ -1,255 +0,0 @@ -{ - "32095784": { - "PMCID": "PMC7039621", - "abstract": null, - "authors": [ - { - "affiliation": "University of Kentucky College of Public Health.", - "author_id": "Anna Hoover", - "firstname": "Anna G", - "initials": "AG", - "lastname": "Hoover" - }, - { - "affiliation": "University of Kentucky Department of Dietetics and Human Nutrition.", - "author_id": "Ann Koempel", - "firstname": "Annie", - "initials": "A", - "lastname": "Koempel" - }, - { - "affiliation": "University of Kentucky College of Public Health.", - "firstname": "W Jay", - "initials": "WJ", - "lastname": "Christian" - }, - { - "affiliation": "University of Kentucky College of Public Health.", - "firstname": "Kimberly I", - "initials": "KI", - "lastname": "Tumlin" - }, - { - "affiliation": "University of Kentucky College of Engineering.", - "author_id": "Kelly Pennell", - "firstname": "Kelly G", - "initials": "KG", - "lastname": "Pennell" - }, - { - "affiliation": "Kentucky Water Resources Research Institute.", - "firstname": "Steven", - "initials": "S", - "lastname": "Evans" - }, - { - "affiliation": "Kentucky Water Resources Research Institute.", - "firstname": "Malissa", - "initials": "M", - "lastname": "McAlister" - }, - { - "affiliation": "University of Kentucky College of Engineering.", - "author_id": "Lindell Ormsbee", - "firstname": "Lindell E", - "initials": "LE", - "lastname": "Ormsbee" - }, - { - "affiliation": "University of Kentucky Department of Dietetics and Human Nutrition.", - "author_id": "Dawn Brewer", - "firstname": "Dawn", - "initials": "D", - "lastname": "Brewer" - } - ], - "conclusions": null, - "copyrights": null, - "doi": null, - "grants": [ - "G08 LM013185", - "P30 ES026529", - "P42 ES007380", - "R01 ES032396" - ], - "journal": "Journal of Appalachian health", - "keywords": [], - "methods": null, - "publication_date": { - "day": 26, - "month": 2, - "year": 2020 - }, - "pubmed_id": "32095784", - "results": null, - "title": "Appalachian Environmental Health Literacy: Building Knowledge and Skills to Protect Health." - }, - "https://doi.org/10.1002/adhm.202101820": { - "PMCID": null, - "abstract": "Humans are constantly exposed to exogenous chemicals throughout their life, which can lead to a multitude of negative health impacts. Advanced materials can play a key role in preventing or mitigating these impacts through a wide variety of applications. The tunable properties of hydrogels and hydrogel nanocomposites (e.g., swelling behavior, biocompatibility, stimuli responsiveness, functionality, etc.) have deemed them ideal platforms for removal of environmental contaminants, detoxification and reduction of body burden from exogenous chemical exposures for prevention of disease initiation, and advanced treatment of chronic diseases, including cancer, diabetes, and cardiovascular disease. In this review, three main junctures where the use of hydrogel and hydrogel nanocomposite materials can intervene to positively impact human health are highlighted: (1) preventing exposures to environmental contaminants; (2) prophylactic treatments to prevent chronic disease initiation; (3) treating chronic diseases after they have developed. This article is protected by copyright. All rights reserved.", - "authors": [ - { - "affiliation": "Department of Chemical and Materials Engineering, University of Kentucky, 177 F Paul Anderson Tower, Lexington, KY, 40506, USA.\nSuperfund Research Center, University of Kentucky, Lexington, KY, 40506, USA.", - "author_id": "Angela Gutierrez", - "firstname": "Angela M", - "initials": "AM", - "lastname": "Gutierrez" - }, - { - "affiliation": "Department of Chemical and Materials Engineering, University of Kentucky, 177 F Paul Anderson Tower, Lexington, KY, 40506, USA.\nSuperfund Research Center, University of Kentucky, Lexington, KY, 40506, USA.", - "firstname": "E Molly", - "initials": "EM", - "lastname": "Frazar" - }, - { - "affiliation": "Department of Chemical and Materials Engineering, University of Kentucky, 177 F Paul Anderson Tower, Lexington, KY, 40506, USA.\nSuperfund Research Center, University of Kentucky, Lexington, KY, 40506, USA.", - "author_id": "Victoria Klaus", - "firstname": "Victoria", - "initials": "V", - "lastname": "Klaus" - }, - { - "affiliation": "Department of Chemical and Materials Engineering, University of Kentucky, 177 F Paul Anderson Tower, Lexington, KY, 40506, USA.\nSuperfund Research Center, University of Kentucky, Lexington, KY, 40506, USA.", - "author_id": "Pranto Paul", - "firstname": "Pranto", - "initials": "P", - "lastname": "Paul" - }, - { - "affiliation": "Department of Chemical and Materials Engineering, University of Kentucky, 177 F Paul Anderson Tower, Lexington, KY, 40506, USA.\nSuperfund Research Center, University of Kentucky, Lexington, KY, 40506, USA.", - "firstname": "J Z", - "initials": "JZ", - "lastname": "Hilt" - } - ], - "conclusions": null, - "copyrights": "This article is protected by copyright. All rights reserved.", - "doi": "10.1002/adhm.202101820", - "grants": [], - "journal": "Advanced healthcare materials", - "keywords": [ - "chronic diseases", - "hydrogel nanocomposites", - "hydrogels", - "remediations", - "therapeutics" - ], - "methods": null, - "publication_date": { - "day": 24, - "month": 11, - "year": 2021 - }, - "pubmed_id": "34811960", - "results": null, - "title": "Hydrogels and Hydrogel Nanocomposites: Enhancing Healthcare Through Human and Environmental Treatment." - }, - "https://doi.org/10.1002/advs.202101999": { - "PMCID": null, - "abstract": "Targeting the epidermal growth factor receptor (EGFR) with tyrosine kinase inhibitors (TKIs) is one of the major precision medicine treatment options for lung adenocarcinoma. Due to common development of drug resistance to first- and second-generation TKIs, third-generation inhibitors, including osimertinib and rociletinib, have been developed. A model of EGFR-driven lung cancer and a method to develop tumors of distinct epigenetic states through 3D organotypic cultures are described here. It is discovered that activation of the EGFR T790M/L858R mutation in lung epithelial cells can drive lung cancers with alveolar or bronchiolar features, which can originate from alveolar type 2 (AT2) cells or bronchioalveolar stem cells, but not basal cells or club cells of the trachea. It is also demonstrated that these clones are able to retain their epigenetic differences through passaging orthotopically in mice and crucially that they have distinct drug vulnerabilities. This work serves as a blueprint for exploring how epigenetics can be used to stratify patients for precision medicine decisions.", - "authors": [ - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Fan", - "initials": "F", - "lastname": "Chen" - }, - { - "affiliation": "Department of Internal Medicine, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Jinpeng", - "initials": "J", - "lastname": "Liu" - }, - { - "affiliation": "Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, 40536, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Robert M", - "initials": "RM", - "lastname": "Flight" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Kassandra J", - "initials": "KJ", - "lastname": "Naughton" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Alexsandr", - "initials": "A", - "lastname": "Lukyanchuk" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Abigail R", - "initials": "AR", - "lastname": "Edgin" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Xiulong", - "initials": "X", - "lastname": "Song" - }, - { - "affiliation": "DNAtrix, 10355 Science Center Drive, Suite 110, San Diego, CA, 92121, USA.", - "firstname": "Haikuo", - "initials": "H", - "lastname": "Zhang" - }, - { - "affiliation": "Laura and Isaac Perlmutter Cancer Center, NYU Langone Medical Center, New York University, New York, NY, 10016, USA.", - "firstname": "Kwok-Kin", - "initials": "KK", - "lastname": "Wong" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.\nDepartment of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, 40536, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.", - "author_id": "Hunter Moseley", - "firstname": "Hunter N B", - "initials": "HNB", - "lastname": "Moseley" - }, - { - "affiliation": "Department of Internal Medicine, University of Kentucky, Lexington, KY, 40536, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Chi", - "initials": "C", - "lastname": "Wang" - }, - { - "affiliation": "Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, 40536, USA.\nMarkey Cancer Center, University of Kentucky, Lexington, KY, 40536, USA.", - "firstname": "Christine F", - "initials": "CF", - "lastname": "Brainson" - } - ], - "conclusions": null, - "copyrights": "\u00a9 2021 The Authors. Advanced Science published by Wiley-VCH GmbH.", - "doi": "10.1002/advs.202101999", - "grants": [ - "NCI K22 CA201036", - "IRG-85-001-25", - "NCI R01 CA237643", - "133123-RSG-19-081-01-TBG", - "NIGMS P20 GM121327-03", - "P30CA177558", - "NIGMS P20 GM121327-03" - ], - "journal": "Advanced science (Weinheim, Baden-Wurttemberg, Germany)", - "keywords": [ - "EGFR", - "alveolar", - "bronchiolar", - "lung cancer", - "organoids" - ], - "methods": null, - "publication_date": { - "day": 9, - "month": 10, - "year": 2021 - }, - "pubmed_id": "34622577", - "results": null, - "title": "Cellular Origins of EGFR-Driven Lung Cancer Cells Determine Sensitivity to Therapy." - } -} \ No newline at end of file diff --git a/tests/testing_files/pubs_by_author_dict_truncated_old.json b/tests/testing_files/pubs_by_author_dict_truncated_old.json deleted file mode 100644 index 3b2cbcb..0000000 --- a/tests/testing_files/pubs_by_author_dict_truncated_old.json +++ /dev/null @@ -1,62 +0,0 @@ -{ - "Angela Gutierrez": 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Medicinal chemistry, metabolic profiling and drug target discovery: A role for metabolic profiling in reverse pharmacology and chemical genetics. Mini-Reviews in Medicinal Chemistry. 2005;5:13\u201320.", + "doi": null, + "pubmed_id": "15638788", + "title": null + }, + { + "PMCID": null, + "citation": "Boros LG. Metabolic targeted therapy of cancer: current tracer technologies and future drug design strategies in the old metabolic network. Metabolomics. 2005;1:11\u201315.", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": null, + "citation": "Fan TWM, Higashi RM, Lane AN. Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metab. Rev. 2006;38:707\u2013732.", + "doi": null, + "pubmed_id": "17145697", + "title": null + }, + { + "PMCID": null, + "citation": "Robertson DG. Metabonomics in toxicology: A review. 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Cancer Cell. 2013;23:316\u2013331.", + "doi": null, + "pubmed_id": "23453623", + "title": null + }, + { + "PMCID": "PMC2903070", + "citation": "Fan TWM, Yuan PX, Lane AN, Higashi RM, Wang Y, Hamidi AB, Zhou RL, Guitart X, Chen G, Manji HK, Kaddurah-Daouk R. Stable isotope-resolved metabolomic analysis of lithium effects on glial-neuronal metabolism and interactions. Metabolomics. 2010;6:165\u2013179.", + "doi": null, + "pubmed_id": "20631920", + "title": null + }, + { + "PMCID": "PMC2475696", + "citation": "Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. Journal of Biological Chemistry. 2008;283:20621\u201320627.", + "doi": null, + "pubmed_id": "18364355", + "title": null + }, + { + "PMCID": null, + "citation": "Vizan P, Boros LG, Figueras A, Capella G, Mangues R, Bassilian S, Lim S, Lee WN, Cascante M. K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", + "doi": null, + "pubmed_id": "15994921", + "title": null + }, + { + "PMCID": null, + "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", + "doi": null, + "pubmed_id": "9612242", + "title": null + }, + { + "PMCID": null, + "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", + "doi": null, + "pubmed_id": "16317166", + "title": null + }, + { + "PMCID": "PMC3109995", + "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. 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Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI TOF/MS) based plant metabolomics. Metabolomics. 2009;5:479\u2013496.", + "doi": null, + "pubmed_id": "20376177", + "title": null + }, + { + "PMCID": null, + "citation": "Fan TW-M. Metabolomics-Edited Transcriptomics Analysis (Meta) In: McQueen CA, editor. Comprehensive Toxicology. Academic Press; Oxford: 2010. pp. 685\u2013706.", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": null, + "citation": "Want EJ, O'Maille G, Smith CA, Brandon TR, Uritboonthai W, Qin C, Trauger SA, Siuzdak G. Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Analytical Chemistry. 2006;78:743\u2013752.", + "doi": null, + "pubmed_id": "16448047", + "title": null + }, + { + "PMCID": null, + "citation": "Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. 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Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", + "doi": null, + "pubmed_id": "17411014", + "title": null + }, + { + "PMCID": null, + "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", + "doi": null, + "pubmed_id": "1514678", + "title": null + }, + { + "PMCID": null, + "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", + "doi": null, + "pubmed_id": "12103361", + "title": null + }, + { + "PMCID": null, + "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. Analytical Biochemistry. 2002;304:220\u2013230.", + "doi": null, + "pubmed_id": "12009699", + "title": null + }, + { + "PMCID": null, + "citation": "Rabinowitz JD, Kimball E. Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal Chem. 2007;79:6167\u20136173.", + "doi": null, + "pubmed_id": "17630720", + "title": null + }, + { + "PMCID": "PMC3477816", + "citation": "Lorkiewicz PK, Higashi RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012 in press.", + "doi": null, + "pubmed_id": "23101002", + "title": null + }, + { + "PMCID": "PMC3501132", + "citation": "Mattingly SJ, Xu T, Nantz MH, Higashi RM, Fan TW-M. A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts. 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This huge increase in usable data requires software capable of correcting the large number of isotopologue peaks resulting from SIRM experiments in a timely manner. We describe the design of a new algorithm and software system capable of handling these high volumes of data, while including quality control methods for maintaining data quality. We validate this new algorithm against a previous single isotope correction algorithm in a two-step cross-validation. Next, we demonstrate the algorithm and correct for the effects of natural abundance for both (13)C and (15)N isotopes on a set of raw isotopologue intensities of UDP-N-acetyl-D-glucosamine derived from a (13)C/(15)N-tracing experiment. 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Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1937;121:235.", + "doi": "10.1016/S0021-9258(18)74342-1", + "pubmed_id": null, + "title": "Deuterium as an indicator in the study of intermediary metabolism" + }, + { + "PMCID": null, + "citation": "Schoenheimer R., Rittenberg D. The study of intermediary metabolism of animals with the aid of isotopes. Physiol. Rev. 1940;20:218.", + "doi": "10.1152/physrev.1940.20.2.218", + "pubmed_id": null, + "title": "The study of intermediary metabolism of animals with the aid of isotopes" + }, + { + "PMCID": null, + "citation": "Schoenheimer R., Rittenberg D. Deuterium as an indicator in the study of intermediary metabolism. J. Biol. Chem. 1935;111:163.", + "doi": "10.1016/S0021-9258(18)75075-8", + "pubmed_id": null, + "title": "Deuterium as an indicator in the study of intermediary metabolism" + }, + { + "PMCID": null, + "citation": "Boros L.G., Brackett D.J., Harrigan G.G. Metabolic biomarker and kinase drug target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP) Curr. Cancer Drug Tar. 2003;3:445\u2013453. doi: 10.2174/1568009033481769.", + "doi": "10.2174/1568009033481769", + "pubmed_id": "14683502", + "title": null + }, + { + "PMCID": "PMC2717907", + "citation": "Fan T.W., Lane A.N., Higashi R.M., Farag M.A., Gao H., Bousamra M., Miller D.M. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol. Cancer. 2009;8:41. doi: 10.1186/1476-4598-8-41.", + "doi": "10.1186/1476-4598-8-41", + "pubmed_id": "19558692", + "title": null + }, + { + "PMCID": "PMC2757635", + "citation": "Lane A.N., Fan T.W.M., Xie Z., Moseley H.N.B., Higashi R.M. Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", + "title": null + }, + { + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", + "title": null + }, + { + "PMCID": null, + "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", + "title": null + }, + { + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", + "title": null + }, + { + "PMCID": null, + "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", + "title": null + }, + { + "PMCID": null, + "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", + "title": null + }, + { + "PMCID": null, + "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", + "doi": null, + "pubmed_id": "10362629", + "title": "Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations" + }, + { + "PMCID": null, + "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", + "title": null + }, + { + "PMCID": "PMC2041839", + "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", + "doi": null, + "pubmed_id": "17583532", + "title": "Efficient calculation of exact mass isotopic distributions" + }, + { + "PMCID": null, + "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", + "title": null + }, + { + "PMCID": null, + "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", + "title": null + }, + { + "PMCID": null, + "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", + "doi": null, + "pubmed_id": "15922621", + "title": "An automated method for the analysis of stable isotope labeling data in proteomics" + }, + { + "PMCID": null, + "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", + "title": null + }, + { + "PMCID": null, + "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. 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Metabolomics. 2007;3:413\u2013426.", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": "PMC2724746", + "citation": "Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457:910\u2013914.", + "doi": null, + "pubmed_id": "19212411", + "title": null + }, + { + "PMCID": null, + "citation": "Griffiths William J., T. K., Wang Yuqin, Kohl Matthias, Enot David P., Deigner H-P. Targeted Metabolomics for Biomarker Discovery. Angew. Chem. Int. Ed. 2010;49:5426\u20135446.", + "doi": null, + "pubmed_id": "20629054", + "title": null + }, + { + "PMCID": null, + "citation": "Theodoridis G, Gika HG, Wilson ID. Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies. Mass Spectrom. Rev. 2011", + "doi": null, + "pubmed_id": "21384411", + "title": null + }, + { + "PMCID": null, + "citation": "Want EJ, Smith CA, Qin CA, VanHorne KC, Siuzdak G. Phospholipid capture combined with non-linear chromatographic correction for improved serum metabolite profiling. Metabolomics. 2006;2:145\u2013154.", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": null, + "citation": "Andrew Clayton T, Lindon JC, Cloarec O, Antti H, Charuel C, Hanton G, Provost J-P, Le Net J-L\u00d8, Baker D, Walley RJ, Everett JR, Nicholson JK. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature. 2006;440:1073\u20131077.", + "doi": null, + "pubmed_id": "16625200", + "title": null + }, + { + "PMCID": null, + "citation": "Harrigan GG, Brackett DJ, Boros LG. Medicinal chemistry, metabolic profiling and drug target discovery: A role for metabolic profiling in reverse pharmacology and chemical genetics. Mini-Reviews in Medicinal Chemistry. 2005;5:13\u201320.", + "doi": null, + "pubmed_id": "15638788", + "title": null + }, + { + "PMCID": null, + "citation": "Boros LG. Metabolic targeted therapy of cancer: current tracer technologies and future drug design strategies in the old metabolic network. Metabolomics. 2005;1:11\u201315.", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": null, + "citation": "Fan TWM, Higashi RM, Lane AN. Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metab. Rev. 2006;38:707\u2013732.", + "doi": null, + "pubmed_id": "17145697", + "title": null + }, + { + "PMCID": null, + "citation": "Robertson DG. Metabonomics in toxicology: A review. Toxicological Sciences. 2005;85:809\u2013822.", + "doi": null, + "pubmed_id": "15689416", + "title": null + }, + { + "PMCID": null, + "citation": "Griffin JL, Bollard ME. Metabonomics: Its potential as a tool in toxicology for safety assessment and data integration. Current Drug Metabolism. 2004;5:389\u2013398.", + "doi": null, + "pubmed_id": "15544433", + "title": null + }, + { + "PMCID": "PMC2140249", + "citation": "Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab. Rev. 2007;39:581\u2013597.", + "doi": null, + "pubmed_id": "17786640", + "title": null + }, + { + "PMCID": "PMC3471671", + "citation": "Fan TWM, Lorkiewicz P, Sellers K, Moseley HNB, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacology & Therapeutics. 2012;133:366\u2013391.", + "doi": null, + "pubmed_id": "22212615", + "title": null + }, + { + "PMCID": null, + "citation": "Lane AN, Fan TW, Higashi RM. Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. 2008;84:541\u2013588.", + "doi": null, + "pubmed_id": "17964943", + "title": null + }, + { + "PMCID": "PMC2717907", + "citation": "Fan TW, Lane AN, Higashi RM, Farag MA, Gao H, Bousamra M, Miller DM. Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM) Mol Cancer. 2009;8:41.", + "doi": null, + "pubmed_id": "19558692", + "title": null + }, + { + "PMCID": "PMC2903070", + "citation": "Fan TW-M, Yuan P, Lane AN, Higashi RM, Wang Y, Hamidi A, Zhou R, Guitart X, Chen G, Manji HKM, Kaddurah-Daouk R. Stable Isotope-Resolved Metabolomic Analysis of Lithium Effects on Glial-Neuronal Metabolism and Interactions. Metabolomics. 2010;6:165\u2013179.", + "doi": null, + "pubmed_id": "20631920", + "title": null + }, + { + "PMCID": null, + "citation": "Zamboni N, Fendt SM, Ruhl M, Sauer U. (13)C-based metabolic flux analysis. Nat Protoc. 2009;4:878\u2013892.", + "doi": null, + "pubmed_id": "19478804", + "title": null + }, + { + "PMCID": "PMC3109995", + "citation": "Fan T, Lane A, Higashi R, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics. 2011;7:257\u2013269.", + "doi": null, + "pubmed_id": "21666826", + "title": null + }, + { + "PMCID": "PMC3126751", + "citation": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T. A novel deconvolution method for modeling UDP-GlcNAc biosynthetic pathways based on 13C mass isotopologue profiles under non steady-state conditions. BMC Biology. 2011;9:37.", + "doi": null, + "pubmed_id": "21627825", + "title": null + }, + { + "PMCID": null, + "citation": "Hiller K, Metallo C, Stephanopoulos G. Elucidation of Cellular Metabolism via Metabolomics and Stable-Isotope Assisted Metabolomics. Current pharmaceutical biotechnology. 2011;12:1075\u20131086.", + "doi": null, + "pubmed_id": "21466455", + "title": null + }, + { + "PMCID": "PMC3087304", + "citation": "Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. Journal of biomolecular NMR. 2011;49:267\u2013280.", + "doi": null, + "pubmed_id": "21350847", + "title": null + }, + { + "PMCID": "PMC3477816", + "citation": "Lorkiewicz PK, Higashii RM, Lane AN, Fan TW-M. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2011", + "doi": null, + "pubmed_id": "23101002", + "title": null + }, + { + "PMCID": "PMC3345194", + "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan TWM, Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. Cell metabolism. 2012;15:110\u2013121.", + "doi": null, + "pubmed_id": "22225880", + "title": null + }, + { + "PMCID": null, + "citation": "Boros LG, Lerner MR, Morgan DL, Taylor SL, Smith BJ, Postier RG, Brackett DJ. [1,2-C-13(2)]-D-glucose profiles of the serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas. 2005;31:337\u2013343.", + "doi": null, + "pubmed_id": "16258367", + "title": null + }, + { + "PMCID": null, + "citation": "Bian F, Kasumov T, Thomas KR, Jobbins KA, David F, Minkler PE, Hoppel CL, Brunengraber H. Peroxisomal and mitochondrial oxidation of fatty acids in the heart, assessed from the C-13 labeling of malonyl-CoA and the acetyl moiety of citrate. Journal of Biological Chemistry. 2005;280:9265\u20139271.", + "doi": null, + "pubmed_id": "15611129", + "title": null + }, + { + "PMCID": "PMC2917841", + "citation": "Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinas M. Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature. 2010;466:774\u2013778.", + "doi": null, + "pubmed_id": "20686576", + "title": null + }, + { + "PMCID": null, + "citation": "Fan TW-M, Lane AN, Higashi RM. The Promise of Metabolomics in Cancer Molecular Therapeutics. Current Opnion in Molecular Therapeutics. 2004;6:584\u2013592.", + "doi": null, + "pubmed_id": "15663322", + "title": null + }, + { + "PMCID": null, + "citation": "Arita M. Personal Communication from metabolome database download", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": "PMC3345194", + "citation": "Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Shusher BS, Zhang H, Zimmerman LJ, Liebler DC, Slebos RJC, Lorkiewicz PK, Higashi RM, Fan Teresa W.M., Dang CV. Glucose-Independent Glutamine Metabolism via TCA Cycling for Proliferation and Survival in B Cells. 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Biochimica et Biophysica Acta. 1986;882:154\u2013167.", + "doi": null, + "pubmed_id": "3011112", + "title": null + }, + { + "PMCID": null, + "citation": "Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol. 2000;18:1157\u20131161.", + "doi": null, + "pubmed_id": "11062433", + "title": null + }, + { + "PMCID": "PMC3746802", + "citation": "Kind T, Meissen JK, Yang D, Nocito F, Vaniya A, Cheng YS, Vandergheynst JS, Fiehn O. Qualitative analysis of algal secretions with multiple mass spectrometric platforms. J Chromatogr A. 2012;1244:139\u2013147.", + "doi": null, + "pubmed_id": "22608776", + "title": null + }, + { + "PMCID": "PMC3430598", + "citation": "Budczies J, Denkert C, Muller BM, Brockmoller SF, Klauschen F, Gyorffy B, Dietel M, Richter-Ehrenstein C, Marten U, Salek RM, Griffin JL, Hilvo M, Oresic M, Wohlgemuth G, Fiehn O. 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K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts. Cancer Res. 2005;65:5512\u20135515.", + "doi": null, + "pubmed_id": "15994921", + "title": null + }, + { + "PMCID": null, + "citation": "Lee WN, Boros LG, Puigjaner J, Bassilian S, Lim S, Cascante M. Mass isotopomer study of the nonoxidative pathways of the pentose cycle with [1,2-13.C2]glucose. Am J Physiol. 1998;274:E843\u2013851.", + "doi": null, + "pubmed_id": "9612242", + "title": null + }, + { + "PMCID": null, + "citation": "Lee WN, Go VL. Nutrient-gene interaction: tracer-based metabolomics. J Nutr. 2005;135:3027S\u20133032S.", + "doi": null, + "pubmed_id": "16317166", + "title": null + }, + { + "PMCID": "PMC3109995", + "citation": "Fan TWM, Lane AN, Higashi RM, Yan J. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. 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Sampling for metabolome analysis of microorganisms. Anal Chem. 2007;79:3843\u20133849.", + "doi": null, + "pubmed_id": "17411014", + "title": null + }, + { + "PMCID": null, + "citation": "de Koning W, van Dam K. A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem. 1992;204:118\u2013123.", + "doi": null, + "pubmed_id": "1514678", + "title": null + }, + { + "PMCID": null, + "citation": "Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomolecular Engineering. 2002;19:5\u201315.", + "doi": null, + "pubmed_id": "12103361", + "title": null + }, + { + "PMCID": null, + "citation": "Daykin CA, Foxall PJD, Connor SC, Lindon JC, Nicholson JK. The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by H-1 nuclear magnetic resonance spectroscopy. 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Acta. 2009;651:201\u2013208. doi: 10.1016/j.aca.2009.08.032.", + "doi": "10.1016/j.aca.2009.08.032", + "pubmed_id": "19782812", + "title": null + }, + { + "PMCID": "PMC2848236", + "citation": "Moseley H.N. Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", + "title": null + }, + { + "PMCID": null, + "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", + "title": null + }, + { + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. 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Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", + "doi": null, + "pubmed_id": "10362629", + "title": "Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations" + }, + { + "PMCID": null, + "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", + "title": null + }, + { + "PMCID": "PMC2041839", + "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. 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Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry. BMC Bioinformatics. 2010;11:139. doi: 10.1186/1471-2105-11-139.", + "doi": "10.1186/1471-2105-11-139", + "pubmed_id": "20236542", + "title": null + }, + { + "PMCID": null, + "citation": "Pingitore F., Tang Y.J., Kruppa G.H., Keasling J.D. Analysis of amino acid isotopomers using FT-ICR MS. Anal. Chem. 2007;79:2483\u20132490. doi: 10.1021/ac061906b.", + "doi": "10.1021/ac061906b", + "pubmed_id": "17305312", + "title": null + }, + { + "PMCID": "PMC3126751", + "citation": "Moseley H.N., Lane A.N., Belshoff A.C., Higashi R.M., Fan T.W. A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions. BMC Biol. 2011;9:37. doi: 10.1186/1741-7007-9-37.", + "doi": "10.1186/1741-7007-9-37", + "pubmed_id": "21627825", + "title": null + }, + { + "PMCID": null, + "citation": "Dauner M., Sauer U. GC-MS Analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 2000;16:642\u2013649. doi: 10.1021/bp000058h.", + "doi": "10.1021/bp000058h", + "pubmed_id": "10933840", + "title": null + }, + { + "PMCID": null, + "citation": "Fischer E., Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 2003;270:880\u2013891. doi: 10.1046/j.1432-1033.2003.03448.x.", + "doi": "10.1046/j.1432-1033.2003.03448.x", + "pubmed_id": "12603321", + "title": null + }, + { + "PMCID": null, + "citation": "Hellerstein M.K., Neese R.A. Mass isotopomer distribution analysis at eight years: Theoretical, analytic, and experimental considerations. Am. J. Physiol.\u2014Endoc. M. 1999;276:E1146\u2013E1170.", + "doi": null, + "pubmed_id": "10362629", + "title": null + }, + { + "PMCID": null, + "citation": "Lee W.N.P., Byerley L.O., Bergner E.A., Edmond J. Mass isotopomer analysis: Theoretical and practical considerations. Biol. Mass Spectrom. 1991;20:451\u2013458. doi: 10.1002/bms.1200200804.", + "doi": "10.1002/bms.1200200804", + "pubmed_id": "1768701", + "title": null + }, + { + "PMCID": "PMC2041839", + "citation": "Snider R. Efficient calculation of exact mass isotopic distributions. JASMS. 2007;18:1511\u20131515.", + "doi": null, + "pubmed_id": "17583532", + "title": null + }, + { + "PMCID": null, + "citation": "Van Winden W., Wittmann C., Heinzle E., Heijnen J. Correcting mass isotopomer distributions for naturally occurring isotopes. Biotechnol. Bioeng. 2002;80:477\u2013479. doi: 10.1002/bit.10393.", + "doi": "10.1002/bit.10393", + "pubmed_id": "12325156", + "title": null + }, + { + "PMCID": null, + "citation": "Wahl S.A., Dauner M., Wiechert W. New tools for mass isotopomer data evaluation in 13C flux analysis: Mass isotope correction, data consistency checking, and precursor relationships. Biotechnol. Bioeng. 2004;85:259\u2013268. doi: 10.1002/bit.10909.", + "doi": "10.1002/bit.10909", + "pubmed_id": "14748080", + "title": null + }, + { + "PMCID": null, + "citation": "Zhang X., Hines W., Adamec J., Asara J., Naylor S., Regnier F. An automated method for the analysis of stable isotope labeling data in proteomics. JASMS. 2005;16:1181\u20131191.", + "doi": null, + "pubmed_id": "15922621", + "title": null + }, + { + "PMCID": null, + "citation": "Fernandez C.A., Des Rosiers C., Previs S.F., David F., Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 1996;31:255\u2013262. doi: 10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.", + "doi": "10.1002/(sici)1096-9888(199603)31:3<255::aid-jms290>3.0.co;2-3", + "pubmed_id": "8799277", + "title": null + }, + { + "PMCID": null, + "citation": "Rockwood A.L., Haimi P. Efficient calculation of accurate masses of isotopic peaks. JASMS. 2006;17:415\u2013419.", + "doi": null, + "pubmed_id": "16458531", + "title": null + }, + { + "PMCID": null, + "citation": "Rockwood A.L., van Orden S.L. Ultrahigh-speed calculation of isotope distributions. Anal. Chem. 1996;68:2027\u20132030. doi: 10.1021/ac951158i.", + "doi": "10.1021/ac951158i", + "pubmed_id": "21619291", + "title": null + }, + { + "PMCID": null, + "citation": "Yergey J.A. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. Ion Phys. 1983;52:337\u2013349. doi: 10.1016/0020-7381(83)85053-0.", + "doi": "10.1016/0020-7381(83)85053-0", + "pubmed_id": null, + "title": null + }, + { + "PMCID": null, + "citation": "Rossum G.V. The Python Programming Language. [(accessed on 21 July 2013)]. Available online: http://www.python.org/", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": null, + "citation": "Sanner M.F. Python: A programming language for software integration and development. J. Mol. Graph. Model. 1999;17:57\u201361.", + "doi": null, + "pubmed_id": "10660911", + "title": null + }, + { + "PMCID": null, + "citation": "Oliphant T.E. A Guide to NumPy. Volume 1. Trelgol Publishing; Spanish Fork, UT, USA: 2006. pp. 1\u2013371.", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": null, + "citation": "Gamma E. Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional; Boston, MA, USA: 1995. pp. 1\u2013416.", + "doi": null, + "pubmed_id": null, + "title": null + }, + { + "PMCID": "PMC3647477", + "citation": "Moseley H.N.B. Error analysis and propagation in metabolomics data analysis. Comp. Struct Biotech. J. 2013;4:e201301006.", + "doi": null, + "pubmed_id": "23667718", + "title": null + }, + { + "PMCID": null, + "citation": "Moseley Bioinformatics Laboratory Software Repository for download. [(accessed on 21 July 2013)]. Available online: http://bioinformatics.cesb.uky.edu/bin/view/Main/SoftwareDevelopment/", + "doi": null, + "pubmed_id": null, + "title": null + } + ], + "results": null, + "title": "A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets." + } +} \ No newline at end of file diff --git a/tests/testing_files/ref_srch_report_tabular1.csv b/tests/testing_files/ref_srch_report_tabular1.csv index ff622ee..1115c2a 100644 --- a/tests/testing_files/ref_srch_report_tabular1.csv +++ b/tests/testing_files/ref_srch_report_tabular1.csv @@ -1,165 +1,165 @@ Authors Grants Abstract Conclusions Copyrights DOI Journal Keywords Methods PMID Results Title PMCID Publication Year Publication Month Publication Day Tok Title Tok DOI Tok PMID Tok Authors Ref Line Comparison First Author Last Author Pub_Authors References -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-015-0068-4 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkx1089 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: ReadTheDocshttps://readthedocs.org/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/0471250953.bi0127s50 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkm957 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/28.1.235 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0879-3 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkm882 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.138 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-007-0070-6 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: GitHubhttps://github.com/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: Python Package Indexhttps://pypi.org/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/s41431-018-0160-0 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2016.18 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-018-1356-6 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkv1042 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0810-y -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gky1033 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: Javascript Object Notation, RFC 4627, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkv1042 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkm882 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-015-0068-4 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkx1089 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: ReadTheDocshttps://readthedocs.org/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/0471250953.bi0127s50 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkm957 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/28.1.235 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0879-3 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gky1033 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0810-y -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.138 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-018-1356-6 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2016.18 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: Javascript Object Notation, RFC 4627, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: Python Package Indexhttps://pypi.org/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: GitHubhttps://github.com/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-007-0070-6 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/s41431-018-0160-0 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu150 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/biot.201600464 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btq223 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1752-0509-3-103 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci3002217 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci00007a012 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bib/bbl022 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: https://doi.org/10.1007/3-540-29782-0_10 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1101/gr.1212003 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1471-2105-14-112 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ac3018795 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/j.pharmthera.2011.12.007 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0882-8 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3390/metabo10030118 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s12859-019-3096-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.4155/bio.13.348 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.73 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3389/fgene.2014.00237 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-3-33 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1741-7007-9-37 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ja036030u -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/acs.jcim.5b00543 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-017-0220-4 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkn582 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/0300-9084(93)90117-B -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1137/14099721X -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.2140/iig.2013.13.135 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2019.23 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-5-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci990322q -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s00214-015-1635-5 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu015 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-3-33 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-5-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2019.23 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3389/fgene.2014.00237 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.2140/iig.2013.13.135 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1137/14099721X -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-017-0220-4 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/0300-9084(93)90117-B -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s00214-015-1635-5 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci990322q -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/acs.jcim.5b00543 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ja036030u -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkn582 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.73 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1471-2105-14-112 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu150 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s10295-015-1585-x -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1741-7007-9-37 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s12859-019-3096-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3390/metabo10030118 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0882-8 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/j.pharmthera.2011.12.007 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ac3018795 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bib/bbl022 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1101/gr.1212003 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: https://doi.org/10.1007/3-540-29782-0_10 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.4155/bio.13.348 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/biot.201600464 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci00007a012 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci3002217 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1752-0509-3-103 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btq223 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu015 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s10295-015-1585-x -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-5-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2019.23 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3389/fgene.2014.00237 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.2140/iig.2013.13.135 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1137/14099721X -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/0300-9084(93)90117-B -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-3-33 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkn582 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci990322q -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/acs.jcim.5b00543 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ja036030u -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s00214-015-1635-5 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-017-0220-4 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.73 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1471-2105-14-112 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1741-7007-9-37 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s12859-019-3096-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3390/metabo10030118 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0882-8 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/j.pharmthera.2011.12.007 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ac3018795 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bib/bbl022 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1101/gr.1212003 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: https://doi.org/10.1007/3-540-29782-0_10 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.4155/bio.13.348 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/biot.201600464 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci00007a012 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci3002217 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1752-0509-3-103 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btq223 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu150 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu015 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s10295-015-1585-x +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-015-0068-4 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkx1089 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: ReadTheDocshttps://readthedocs.org/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/0471250953.bi0127s50 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkm957 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/28.1.235 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0879-3 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkm882 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.138 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-007-0070-6 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: GitHubhttps://github.com/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: Python Package Indexhttps://pypi.org/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/s41431-018-0160-0 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2016.18 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-018-1356-6 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkv1042 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0810-y +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gky1033 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: Javascript Object Notation, RFC 4627, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkv1042 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkm882 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-015-0068-4 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkx1089 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: ReadTheDocshttps://readthedocs.org/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/0471250953.bi0127s50 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkm957 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/28.1.235 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0879-3 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gky1033 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0810-y +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.138 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-018-1356-6 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2016.18 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: Javascript Object Notation, RFC 4627, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: Python Package Indexhttps://pypi.org/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: GitHubhttps://github.com/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-007-0070-6 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/s41431-018-0160-0 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163. N/A Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu150 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/biot.201600464 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btq223 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1752-0509-3-103 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci3002217 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci00007a012 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bib/bbl022 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: 10.1007/3-540-29782-0_10 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1101/gr.1212003 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1471-2105-14-112 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ac3018795 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/j.pharmthera.2011.12.007 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0882-8 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3390/metabo10030118 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s12859-019-3096-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.4155/bio.13.348 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.73 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3389/fgene.2014.00237 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-3-33 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1741-7007-9-37 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ja036030u +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/acs.jcim.5b00543 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-017-0220-4 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkn582 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/0300-9084(93)90117-B +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1137/14099721X +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.2140/iig.2013.13.135 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2019.23 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-5-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci990322q +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s00214-015-1635-5 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu015 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-3-33 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-5-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2019.23 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3389/fgene.2014.00237 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.2140/iig.2013.13.135 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1137/14099721X +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-017-0220-4 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/0300-9084(93)90117-B +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s00214-015-1635-5 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci990322q +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/acs.jcim.5b00543 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ja036030u +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkn582 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.73 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1471-2105-14-112 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu150 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s10295-015-1585-x +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1741-7007-9-37 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s12859-019-3096-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3390/metabo10030118 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0882-8 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/j.pharmthera.2011.12.007 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ac3018795 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bib/bbl022 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1101/gr.1212003 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: 10.1007/3-540-29782-0_10 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.4155/bio.13.348 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/biot.201600464 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci00007a012 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci3002217 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1752-0509-3-103 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btq223 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu015 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s10295-015-1585-x +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-5-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2019.23 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3389/fgene.2014.00237 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.2140/iig.2013.13.135 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1137/14099721X +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/0300-9084(93)90117-B +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-3-33 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkn582 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci990322q +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/acs.jcim.5b00543 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ja036030u +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s00214-015-1635-5 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-017-0220-4 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.73 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1471-2105-14-112 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1741-7007-9-37 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s12859-019-3096-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3390/metabo10030118 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0882-8 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/j.pharmthera.2011.12.007 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ac3018795 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bib/bbl022 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1101/gr.1212003 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: 10.1007/3-540-29782-0_10 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.4155/bio.13.348 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/biot.201600464 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci00007a012 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci3002217 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1752-0509-3-103 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btq223 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu150 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu015 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368. N/A Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s10295-015-1585-x diff --git a/tests/testing_files/ref_srch_report_tabular2.csv b/tests/testing_files/ref_srch_report_tabular2.csv index b12fb8f..23d1ab6 100644 --- a/tests/testing_files/ref_srch_report_tabular2.csv +++ b/tests/testing_files/ref_srch_report_tabular2.csv @@ -1,165 +1,165 @@ Authors Grants Abstract Conclusions Copyrights DOI Journal Keywords Methods PMID Results Title PMCID Publication Year Publication Month Publication Day Tok Title Tok DOI Tok PMID Tok Authors Ref Line Comparison First Author Last Author Pub_Authors References -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-015-0068-4 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkx1089 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: ReadTheDocshttps://readthedocs.org/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/0471250953.bi0127s50 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkm957 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/28.1.235 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0879-3 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkm882 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.138 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-007-0070-6 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: GitHubhttps://github.com/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: Python Package Indexhttps://pypi.org/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/s41431-018-0160-0 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2016.18 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-018-1356-6 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkv1042 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0810-y -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gky1033 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: Javascript Object Notation, RFC 4627, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkv1042 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkm882 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-015-0068-4 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkx1089 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: ReadTheDocshttps://readthedocs.org/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/0471250953.bi0127s50 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkm957 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/28.1.235 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0879-3 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gky1033 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0810-y -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.138 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-018-1356-6 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2016.18 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: Javascript Object Notation, RFC 4627, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: Python Package Indexhttps://pypi.org/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: GitHubhttps://github.com/, Title: None, PMID: None, PMCID: None, DOI: None -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-007-0070-6 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/s41431-018-0160-0 -Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu150 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/biot.201600464 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btq223 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1752-0509-3-103 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci3002217 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci00007a012 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bib/bbl022 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: https://doi.org/10.1007/3-540-29782-0_10 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1101/gr.1212003 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1471-2105-14-112 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ac3018795 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/j.pharmthera.2011.12.007 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0882-8 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3390/metabo10030118 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s12859-019-3096-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.4155/bio.13.348 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.73 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3389/fgene.2014.00237 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-3-33 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1741-7007-9-37 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ja036030u -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/acs.jcim.5b00543 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-017-0220-4 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkn582 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/0300-9084(93)90117-B -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1137/14099721X -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.2140/iig.2013.13.135 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2019.23 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-5-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci990322q -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s00214-015-1635-5 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu015 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-3-33 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-5-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2019.23 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3389/fgene.2014.00237 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.2140/iig.2013.13.135 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1137/14099721X -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-017-0220-4 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/0300-9084(93)90117-B -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s00214-015-1635-5 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci990322q -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/acs.jcim.5b00543 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ja036030u -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkn582 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.73 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1471-2105-14-112 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu150 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s10295-015-1585-x -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1741-7007-9-37 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s12859-019-3096-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3390/metabo10030118 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0882-8 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/j.pharmthera.2011.12.007 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ac3018795 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bib/bbl022 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1101/gr.1212003 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: https://doi.org/10.1007/3-540-29782-0_10 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.4155/bio.13.348 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/biot.201600464 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci00007a012 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci3002217 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1752-0509-3-103 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btq223 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu015 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s10295-015-1585-x -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-5-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2019.23 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3389/fgene.2014.00237 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.2140/iig.2013.13.135 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1137/14099721X -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/0300-9084(93)90117-B -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1758-2946-3-33 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/nar/gkn582 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci990322q -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/acs.jcim.5b00543 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ja036030u -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s00214-015-1635-5 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s13321-017-0220-4 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1038/sdata.2017.73 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1471-2105-14-112 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1741-7007-9-37 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/s12859-019-3096-7 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.3390/metabo10030118 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s11306-015-0882-8 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1016/j.pharmthera.2011.12.007 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ac3018795 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bib/bbl022 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1101/gr.1212003 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: https://doi.org/10.1007/3-540-29782-0_10 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.4155/bio.13.348 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1002/biot.201600464 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci00007a012 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1021/ci3002217 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1186/1752-0509-3-103 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btq223 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu150 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1093/bioinformatics/btu015 -Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: https://doi.org/10.1007/s10295-015-1585-x +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-015-0068-4 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkx1089 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: ReadTheDocshttps://readthedocs.org/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/0471250953.bi0127s50 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkm957 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/28.1.235 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0879-3 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkm882 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.138 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-007-0070-6 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: GitHubhttps://github.com/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: Python Package Indexhttps://pypi.org/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/s41431-018-0160-0 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2016.18 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-018-1356-6 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkv1042 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0810-y +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gky1033 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: None, Title: Javascript Object Notation, RFC 4627, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkv1042 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Powell, Christian D. None None Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkm882 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-015-0068-4 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkx1089 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: ReadTheDocshttps://readthedocs.org/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/0471250953.bi0127s50 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkm957 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/28.1.235 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0879-3 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gky1033 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0810-y +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.138 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-018-1356-6 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2016.18 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: Javascript Object Notation, RFC 4627, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: Python Package Indexhttps://pypi.org/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: GitHubhttps://github.com/, Title: None, PMID: None, PMCID: None, DOI: None +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-007-0070-6 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/s41431-018-0160-0 +Christian D. Powell, Hunter N.B. Moseley P42ES007380, R03OD030603, 1419282, 2020026 None None None 10.3390/metabo11030163 MDPI AG None None None None The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository None 2021 3 12 The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. 10.3390/metabo11030163 None Powell C, Moseley H N/A True Powell, Christian D. Moseley, Hunter N.B. Moseley, Hunter N.B. None None Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu150 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/biot.201600464 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btq223 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1752-0509-3-103 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci3002217 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci00007a012 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bib/bbl022 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: 10.1007/3-540-29782-0_10 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1101/gr.1212003 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1471-2105-14-112 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ac3018795 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/j.pharmthera.2011.12.007 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0882-8 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3390/metabo10030118 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s12859-019-3096-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.4155/bio.13.348 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.73 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3389/fgene.2014.00237 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-3-33 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1741-7007-9-37 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ja036030u +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/acs.jcim.5b00543 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-017-0220-4 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkn582 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/0300-9084(93)90117-B +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1137/14099721X +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.2140/iig.2013.13.135 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2019.23 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-5-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci990322q +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s00214-015-1635-5 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu015 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-3-33 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-5-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2019.23 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3389/fgene.2014.00237 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.2140/iig.2013.13.135 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1137/14099721X +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-017-0220-4 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/0300-9084(93)90117-B +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s00214-015-1635-5 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci990322q +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/acs.jcim.5b00543 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ja036030u +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkn582 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.73 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1471-2105-14-112 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu150 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s10295-015-1585-x +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1741-7007-9-37 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s12859-019-3096-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3390/metabo10030118 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0882-8 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/j.pharmthera.2011.12.007 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ac3018795 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bib/bbl022 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1101/gr.1212003 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: 10.1007/3-540-29782-0_10 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.4155/bio.13.348 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/biot.201600464 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci00007a012 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci3002217 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1752-0509-3-103 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btq223 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu015 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Jin, Huan None None Citation: None, Title: Introduction to Algorithms, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s10295-015-1585-x +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-5-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2019.23 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3389/fgene.2014.00237 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.2140/iig.2013.13.135 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1137/14099721X +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/0300-9084(93)90117-B +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1758-2946-3-33 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/nar/gkn582 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci990322q +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version), PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/acs.jcim.5b00543 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: The JavaScript Object Notation (JSON) Data Interchange Formathttps://www.rfc-editor.org/info/rfc7159, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ja036030u +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724, Title: None, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s00214-015-1635-5 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s13321-017-0220-4 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1038/sdata.2017.73 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1471-2105-14-112 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1741-7007-9-37 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/s12859-019-3096-7 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.3390/metabo10030118 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s11306-015-0882-8 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1016/j.pharmthera.2011.12.007 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ac3018795 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bib/bbl022 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1101/gr.1212003 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM), PMID: None, PMCID: None, DOI: 10.1007/3-540-29782-0_10 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.4155/bio.13.348 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1002/biot.201600464 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci00007a012 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions, PMID: None, PMCID: None, DOI: None +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1021/ci3002217 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1186/1752-0509-3-103 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btq223 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu150 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Mitchell, Joshua M. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1093/bioinformatics/btu015 +Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley 1419282 None None None 10.3390/metabo10090368 MDPI AG None None None None Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases None 2020 9 11 Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. 10.3390/metabo10090368 None Jin H, Mitchell J, Moseley H N/A False Jin, Huan Moseley, Hunter N. B. Moseley, Hunter N. B. None None Citation: None, Title: None, PMID: None, PMCID: None, DOI: 10.1007/s10295-015-1585-x diff --git a/tests/testing_files/ref_srch_report_tabular3.csv b/tests/testing_files/ref_srch_report_tabular3.csv index cdd9099..e8c9983 100644 --- a/tests/testing_files/ref_srch_report_tabular3.csv +++ b/tests/testing_files/ref_srch_report_tabular3.csv @@ -1,6 +1,6 @@ Authors,Grants,Abstract,Conclusions,Copyrights,DOI,Journal,Keywords,Methods,PMID,Results,Title,PMCID,Publication Year,Publication Month,Publication Day,Tok Title,Tok DOI,Tok PMID,Tok Authors,Ref Line,Comparison,First Author,Last Author,Pub_Authors -"Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley",1419282,None,None,None,10.3390/metabo10090368,MDPI AG,None,None,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases,None,2020,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.,10.3390/metabo10090368,None,"Jin H, Mitchell J, Moseley H","Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368.",N/A,"Jin, Huan","Moseley, Hunter N. B.","Jin, Huan None None" -"Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley",1419282,None,None,None,10.3390/metabo10090368,MDPI AG,None,None,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases,None,2020,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.,10.3390/metabo10090368,None,"Jin H, Mitchell J, Moseley H","Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368.",N/A,"Jin, Huan","Moseley, Hunter N. B.","Mitchell, Joshua M. None None" -"Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley",1419282,None,None,None,10.3390/metabo10090368,MDPI AG,None,None,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases,None,2020,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.,10.3390/metabo10090368,None,"Jin H, Mitchell J, Moseley H","Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368.",N/A,"Jin, Huan","Moseley, Hunter N. B.","Moseley, Hunter N. B. None None" -"Christian D. Powell, Hunter N.B. Moseley","P42ES007380, R03OD030603, 1419282, 2020026",None,None,None,10.3390/metabo11030163,MDPI AG,None,None,None,None,"The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository",None,2021,None,None,"The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository.",10.3390/metabo11030163,None,"Powell C, Moseley H","Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163.",N/A,"Powell, Christian D.","Moseley, Hunter N.B.","Powell, Christian D. None None" -"Christian D. Powell, Hunter N.B. Moseley","P42ES007380, R03OD030603, 1419282, 2020026",None,None,None,10.3390/metabo11030163,MDPI AG,None,None,None,None,"The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository",None,2021,None,None,"The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository.",10.3390/metabo11030163,None,"Powell C, Moseley H","Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163.",N/A,"Powell, Christian D.","Moseley, Hunter N.B.","Moseley, Hunter N.B. None None" +"Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley",1419282,None,None,None,10.3390/metabo10090368,MDPI AG,None,None,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases,None,2020,9,11,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.,10.3390/metabo10090368,None,"Jin H, Mitchell J, Moseley H","Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368.",N/A,"Jin, Huan","Moseley, Hunter N. B.","Jin, Huan None None" +"Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley",1419282,None,None,None,10.3390/metabo10090368,MDPI AG,None,None,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases,None,2020,9,11,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.,10.3390/metabo10090368,None,"Jin H, Mitchell J, Moseley H","Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368.",N/A,"Jin, Huan","Moseley, Hunter N. B.","Mitchell, Joshua M. None None" +"Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley",1419282,None,None,None,10.3390/metabo10090368,MDPI AG,None,None,None,None,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases,None,2020,9,11,Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.,10.3390/metabo10090368,None,"Jin H, Mitchell J, Moseley H","Jin H, Mitchell J, Moseley H. Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368.",N/A,"Jin, Huan","Moseley, Hunter N. B.","Moseley, Hunter N. B. None None" +"Christian D. Powell, Hunter N.B. Moseley","P42ES007380, R03OD030603, 1419282, 2020026",None,None,None,10.3390/metabo11030163,MDPI AG,None,None,None,None,"The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository",None,2021,3,12,"The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository.",10.3390/metabo11030163,None,"Powell C, Moseley H","Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163.",N/A,"Powell, Christian D.","Moseley, Hunter N.B.","Powell, Christian D. None None" +"Christian D. Powell, Hunter N.B. Moseley","P42ES007380, R03OD030603, 1419282, 2020026",None,None,None,10.3390/metabo11030163,MDPI AG,None,None,None,None,"The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository",None,2021,3,12,"The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository.",10.3390/metabo11030163,None,"Powell C, Moseley H","Powell C, Moseley H. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163.",N/A,"Powell, Christian D.","Moseley, Hunter N.B.","Moseley, Hunter N.B. 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zLjACYTd5e?zykT>ENxbM?t^&TtE3U{i!)u$XFLz9*p%cHzVgVOat~E~mnk^1X(gnh zS%1EM*L@90$Kwnr-<&QeZ2i~p$Vd(YF9PuoKEk%+{Z;jh93B6sc?gyJ<9Zh-=CBCH z4mm`*qQ!<&3cyvc151o$wa&_okm71B6!T58D<6fIyxE(5T{}KC@3j-X?(K0UDF>$# zG&qYL?@@`^$RPrvQreJSBzVlh_56r|aTqnnk45QY0=`Ha_^75)5t=#&0A)~1B%$$| zsyTMqT=j+m`K~z1?09RQhGK z9hy(&)zMDmH9J<*FY}VIT>L%kv~n)(@X+4LpD_p#hF731PDRxy%RU$B`4Pnq$d0p3 z4mA<@He&NlickK<`&GcNr>s8(h>`vj@aLK9SLm;i<)6@Sir=BX#+m<+@HhAQCmsOU rpauZ`;Y@#p|J?-s6>j+8FYrGMq6!p<*j)es6Y&c`_-opSzuo;G7(cke diff --git a/tests/testing_files/ref_srch_report_test1.txt b/tests/testing_files/ref_srch_report_test1.txt index 3a47d1e..1393f04 100644 --- a/tests/testing_files/ref_srch_report_test1.txt +++ b/tests/testing_files/ref_srch_report_test1.txt @@ -12,8 +12,8 @@ Results: None Title: Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases PMCID: None Publication Year: 2020 -Publication Month: None -Publication Day: None +Publication Month: 9 +Publication Day: 11 Tok Title: Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Tok DOI: 10.3390/metabo10090368 Tok PMID: None @@ -31,85 +31,85 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/bioinformatics/btu015 +DOI: 10.1093/bioinformatics/btu015 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s10295-015-1585-x +DOI: 10.1007/s10295-015-1585-x Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1741-7007-9-37 +DOI: 10.1186/1741-7007-9-37 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/s12859-019-3096-7 +DOI: 10.1186/s12859-019-3096-7 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3390/metabo10030118 +DOI: 10.3390/metabo10030118 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-015-0882-8 +DOI: 10.1007/s11306-015-0882-8 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.pharmthera.2011.12.007 +DOI: 10.1016/j.pharmthera.2011.12.007 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ac3018795 +DOI: 10.1021/ac3018795 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/bib/bbl022 +DOI: 10.1093/bib/bbl022 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1101/gr.1212003 +DOI: 10.1101/gr.1212003 Citation: None Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM) PMID: None PMCID: None -DOI: https://doi.org/10.1007/3-540-29782-0_10 +DOI: 10.1007/3-540-29782-0_10 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.4155/bio.13.348 +DOI: 10.4155/bio.13.348 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/biot.201600464 +DOI: 10.1002/biot.201600464 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ci00007a012 +DOI: 10.1021/ci00007a012 Citation: None Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions @@ -121,79 +121,79 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ci3002217 +DOI: 10.1021/ci3002217 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1752-0509-3-103 +DOI: 10.1186/1752-0509-3-103 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/bioinformatics/btq223 +DOI: 10.1093/bioinformatics/btq223 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/bioinformatics/btu150 +DOI: 10.1093/bioinformatics/btu150 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1471-2105-14-112 +DOI: 10.1186/1471-2105-14-112 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2017.73 +DOI: 10.1038/sdata.2017.73 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/s13321-017-0220-4 +DOI: 10.1186/s13321-017-0220-4 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1758-2946-3-33 +DOI: 10.1186/1758-2946-3-33 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1758-2946-5-7 +DOI: 10.1186/1758-2946-5-7 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2019.23 +DOI: 10.1038/sdata.2019.23 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3389/fgene.2014.00237 +DOI: 10.3389/fgene.2014.00237 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.2140/iig.2013.13.135 +DOI: 10.2140/iig.2013.13.135 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1137/14099721X +DOI: 10.1137/14099721X Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html Title: None @@ -205,25 +205,25 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/0300-9084(93)90117-B +DOI: 10.1016/0300-9084(93)90117-B Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkn582 +DOI: 10.1093/nar/gkn582 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s00214-015-1635-5 +DOI: 10.1007/s00214-015-1635-5 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ci990322q +DOI: 10.1021/ci990322q Citation: None Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version) @@ -235,7 +235,7 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.jcim.5b00543 +DOI: 10.1021/acs.jcim.5b00543 Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile Title: None @@ -253,7 +253,7 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ja036030u +DOI: 10.1021/ja036030u Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724 Title: None @@ -282,8 +282,8 @@ Results: None Title: The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository PMCID: None Publication Year: 2021 -Publication Month: None -Publication Day: None +Publication Month: 3 +Publication Day: 12 Tok Title: The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Tok DOI: 10.3390/metabo11030163 Tok PMID: None @@ -300,7 +300,7 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkv1042 +DOI: 10.1093/nar/gkv1042 Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259 Title: None @@ -318,19 +318,19 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-018-1356-6 +DOI: 10.1007/s11306-018-1356-6 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2016.18 +DOI: 10.1038/sdata.2016.18 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41431-018-0160-0 +DOI: 10.1038/s41431-018-0160-0 Citation: Python Package Indexhttps://pypi.org/ Title: None @@ -348,37 +348,37 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-007-0070-6 +DOI: 10.1007/s11306-007-0070-6 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-015-0810-y +DOI: 10.1007/s11306-015-0810-y Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2017.138 +DOI: 10.1038/sdata.2017.138 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-015-0879-3 +DOI: 10.1007/s11306-015-0879-3 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/28.1.235 +DOI: 10.1093/nar/28.1.235 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkm957 +DOI: 10.1093/nar/gkm957 Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score Title: None @@ -390,7 +390,7 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/0471250953.bi0127s50 +DOI: 10.1002/0471250953.bi0127s50 Citation: ReadTheDocshttps://readthedocs.org/ Title: None @@ -402,25 +402,25 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkx1089 +DOI: 10.1093/nar/gkx1089 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/s13321-015-0068-4 +DOI: 10.1186/s13321-015-0068-4 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkm882 +DOI: 10.1093/nar/gkm882 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gky1033 +DOI: 10.1093/nar/gky1033 Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/ Title: None diff --git a/tests/testing_files/ref_srch_report_test2.txt b/tests/testing_files/ref_srch_report_test2.txt index 6544d0f..95d6d23 100644 --- a/tests/testing_files/ref_srch_report_test2.txt +++ b/tests/testing_files/ref_srch_report_test2.txt @@ -12,8 +12,8 @@ Results: None Title: Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases PMCID: None Publication Year: 2020 -Publication Month: None -Publication Day: None +Publication Month: 9 +Publication Day: 11 Tok Title: Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases. Tok DOI: 10.3390/metabo10090368 Tok PMID: None @@ -31,85 +31,85 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/bioinformatics/btu015 +DOI: 10.1093/bioinformatics/btu015 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s10295-015-1585-x +DOI: 10.1007/s10295-015-1585-x Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1741-7007-9-37 +DOI: 10.1186/1741-7007-9-37 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/s12859-019-3096-7 +DOI: 10.1186/s12859-019-3096-7 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3390/metabo10030118 +DOI: 10.3390/metabo10030118 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-015-0882-8 +DOI: 10.1007/s11306-015-0882-8 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/j.pharmthera.2011.12.007 +DOI: 10.1016/j.pharmthera.2011.12.007 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ac3018795 +DOI: 10.1021/ac3018795 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/bib/bbl022 +DOI: 10.1093/bib/bbl022 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1101/gr.1212003 +DOI: 10.1101/gr.1212003 Citation: None Title: Map Editor for the Atomic Reconstruction of Metabolism (ARM) PMID: None PMCID: None -DOI: https://doi.org/10.1007/3-540-29782-0_10 +DOI: 10.1007/3-540-29782-0_10 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.4155/bio.13.348 +DOI: 10.4155/bio.13.348 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/biot.201600464 +DOI: 10.1002/biot.201600464 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ci00007a012 +DOI: 10.1021/ci00007a012 Citation: None Title: RPAIR: A reactant-pair database representing chemical changes in enzymatic reactions @@ -121,79 +121,79 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ci3002217 +DOI: 10.1021/ci3002217 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1752-0509-3-103 +DOI: 10.1186/1752-0509-3-103 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/bioinformatics/btq223 +DOI: 10.1093/bioinformatics/btq223 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/bioinformatics/btu150 +DOI: 10.1093/bioinformatics/btu150 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1471-2105-14-112 +DOI: 10.1186/1471-2105-14-112 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2017.73 +DOI: 10.1038/sdata.2017.73 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/s13321-017-0220-4 +DOI: 10.1186/s13321-017-0220-4 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1758-2946-3-33 +DOI: 10.1186/1758-2946-3-33 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/1758-2946-5-7 +DOI: 10.1186/1758-2946-5-7 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2019.23 +DOI: 10.1038/sdata.2019.23 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.3389/fgene.2014.00237 +DOI: 10.3389/fgene.2014.00237 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.2140/iig.2013.13.135 +DOI: 10.2140/iig.2013.13.135 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1137/14099721X +DOI: 10.1137/14099721X Citation: Indigo Toolkithttps://lifescience.opensource.epam.com/indigo/index.html Title: None @@ -205,25 +205,25 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1016/0300-9084(93)90117-B +DOI: 10.1016/0300-9084(93)90117-B Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkn582 +DOI: 10.1093/nar/gkn582 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s00214-015-1635-5 +DOI: 10.1007/s00214-015-1635-5 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ci990322q +DOI: 10.1021/ci990322q Citation: None Title: Algebraic Combinatorics in Mathematical Chemistry. Methods and Algorithms. III, Graph Invariants and Stabilization Methods (Preliminary Version) @@ -235,7 +235,7 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/acs.jcim.5b00543 +DOI: 10.1021/acs.jcim.5b00543 Citation: Ctfilehttps://github.com/MoseleyBioinformaticsLab/ctfile Title: None @@ -253,7 +253,7 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1021/ja036030u +DOI: 10.1021/ja036030u Citation: Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerismhttps://arxiv.org/abs/1303.1724 Title: None @@ -282,8 +282,8 @@ Results: None Title: The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository PMCID: None Publication Year: 2021 -Publication Month: None -Publication Day: None +Publication Month: 3 +Publication Day: 12 Tok Title: The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Tok DOI: 10.3390/metabo11030163 Tok PMID: None @@ -300,7 +300,7 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkv1042 +DOI: 10.1093/nar/gkv1042 Citation: The Javascript Object Notation (Json) Data Interchange Format (No. RFC 8259)https://tools.ietf.org/html/rfc8259 Title: None @@ -318,19 +318,19 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-018-1356-6 +DOI: 10.1007/s11306-018-1356-6 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2016.18 +DOI: 10.1038/sdata.2016.18 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/s41431-018-0160-0 +DOI: 10.1038/s41431-018-0160-0 Citation: Python Package Indexhttps://pypi.org/ Title: None @@ -348,37 +348,37 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-007-0070-6 +DOI: 10.1007/s11306-007-0070-6 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-015-0810-y +DOI: 10.1007/s11306-015-0810-y Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1038/sdata.2017.138 +DOI: 10.1038/sdata.2017.138 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1007/s11306-015-0879-3 +DOI: 10.1007/s11306-015-0879-3 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/28.1.235 +DOI: 10.1093/nar/28.1.235 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkm957 +DOI: 10.1093/nar/gkm957 Citation: UniProt Annotation Scorehttps://www.uniprot.org/help/annotation_score Title: None @@ -390,7 +390,7 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1002/0471250953.bi0127s50 +DOI: 10.1002/0471250953.bi0127s50 Citation: ReadTheDocshttps://readthedocs.org/ Title: None @@ -402,25 +402,25 @@ Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkx1089 +DOI: 10.1093/nar/gkx1089 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1186/s13321-015-0068-4 +DOI: 10.1186/s13321-015-0068-4 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gkm882 +DOI: 10.1093/nar/gkm882 Citation: None Title: None PMID: None PMCID: None -DOI: https://doi.org/10.1093/nar/gky1033 +DOI: 10.1093/nar/gky1033 Citation: Sphinx: Python Documentation Generatorhttps://www.sphinx-doc.org/en/master/ Title: None diff --git a/tests/testing_files/solo_Crossref.json b/tests/testing_files/solo_Crossref.json index a9c1a66..74c3f8d 100644 --- a/tests/testing_files/solo_Crossref.json +++ b/tests/testing_files/solo_Crossref.json @@ -59,8 +59,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 16, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -78,21 +78,21 @@ { "PMCID": null, "citation": "Da Silva, B. F., Ahmadireskety, A., Aristizabal-Henao, J. J. & Bowden, J. A. A rapid and simple method to quantify per-and polyfluoroalkyl substances (PFAS) in plasma and serum using 96-well plates. MethodsX. 7, 101111\u201310111 (2020).", - "doi": "https://doi.org/10.1016/j.mex.2020.101111", + "doi": "10.1016/j.mex.2020.101111", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hagstrom, A. L. et al. Yale School of Public Health Symposium: an overview of the challenges and opportunities associated with per-and polyfluoroalkyl substances (PFAS). Sci. Total Envir. 778, 146192 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2021.146192", + "doi": "10.1016/j.scitotenv.2021.146192", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Groffen, T. et al. A rapid method for the detection and quantification of legacy and emerging per-and polyfluoroalkyl substances (PFAS) in bird feathers using UPLC-MS/MS. J. Chromatogr. B. 1172, 122653 (2021).", - "doi": "https://doi.org/10.1016/j.jchromb.2021.122653", + "doi": "10.1016/j.jchromb.2021.122653", "pubmed_id": null, "title": null }, @@ -106,98 +106,98 @@ { "PMCID": null, "citation": "Rogers, R. D., Reh, C. M. & Breysse, P. Advancing per-and polyfluoroalkyl substances (PFAS) research: an overview of ATSDR and NCEH activities and recommendations. J. Exp. Sci. Envir. Epi. 31, 961\u2013971 (2021).", - "doi": "https://doi.org/10.1038/s41370-021-00316-6", + "doi": "10.1038/s41370-021-00316-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hauk\u00e5s, M., Berger, U., Hop, H., Gulliksen, B. & Gabrielsen, G. W. Bioaccumulation of per-and polyfluorinated alkyl substances (PFAS) in selected species from the Barents Sea food web. Envir. Poll. 148, 360\u2013371 (2007).", - "doi": "https://doi.org/10.1016/j.envpol.2006.09.021", + "doi": "10.1016/j.envpol.2006.09.021", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Fenton, S. E. et al. Per\u2010and polyfluoroalkyl substance toxicity and human health review: Current state of knowledge and strategies for informing future research. Envir. Tox. Chem. 40, 606\u2013630 (2021).", - "doi": "https://doi.org/10.1002/etc.4890", + "doi": "10.1002/etc.4890", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Kucharzyk, K. H., Darlington, R., Benotti, M., Deeb, R. & Hawley, E. Novel treatment technologies for PFAS compounds: A critical review. J. Environ. Manage. 204, 757\u2013764 (2017).", - "doi": "https://doi.org/10.1016/j.jenvman.2017.08.016", + "doi": "10.1016/j.jenvman.2017.08.016", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "National Academies of Sciences, Engineering, and Medicine (NASEM), Guidance on PFAS Exposure, Testing, and Clinical Follow-Up. Washington, DC: The National Academies Press. https://doi.org/10.17226/26156 (2022).", - "doi": "https://doi.org/10.17226/26156", + "doi": "10.17226/26156", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Rahman, M. F., Peldszus, S. & Anderson, W. B. Behaviour and fate of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in drinking water treatment: A review. Water Res. 50, 318\u2013340 (2014).", - "doi": "https://doi.org/10.1016/j.watres.2013.10.045", + "doi": "10.1016/j.watres.2013.10.045", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "De Silva, A. O. et al. PFAS exposure pathways for humans and wildlife: a synthesis of current knowledge and key gaps in understanding. Environ. Tox. Chem. 40, 631\u2013657 (2021).", - "doi": "https://doi.org/10.1002/etc.4935", + "doi": "10.1002/etc.4935", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Olsen, G. W. et al. Per-and polyfluoroalkyl substances (PFAS) in American Red Cross adult blood donors, 2000\u20132015. Environ. Res. 157, 87\u201395 (2017).", - "doi": "https://doi.org/10.1016/j.envres.2017.05.013", + "doi": "10.1016/j.envres.2017.05.013", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Domingo, J. L. & Nadal, M. Human exposure to per-and polyfluoroalkyl substances (PFAS) through drinking water: a review of the recent scientific literature. Environ. Res. 177, 108648\u2013108648 (2019).", - "doi": "https://doi.org/10.1016/j.envres.2019.108648", + "doi": "10.1016/j.envres.2019.108648", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hepburn, E. et al. Contamination of groundwater with per-and polyfluoroalkyl substances (PFAS) from legacy landfills in an urban re-development precinct. Environ. Poll. 248, 101\u2013113 (2019).", - "doi": "https://doi.org/10.1016/j.envpol.2019.02.018", + "doi": "10.1016/j.envpol.2019.02.018", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Bai, X. & Son, Y. Perfluoroalkyl substances (PFAS) in surface water and sediments from two urban watersheds in Nevada, USA. Sci. Tot. Envir. 751, 141622\u2013141622 (2021).", - "doi": "https://doi.org/10.1016/j.scitotenv.2020.141622", + "doi": "10.1016/j.scitotenv.2020.141622", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Li, Y. et al. Formation and fate of perfluoroalkyl acids (PFAAs) in a laboratory-scale urban wastewater system. Water Res. 216, 118295\u2013118295 (2022).", - "doi": "https://doi.org/10.1016/j.watres.2022.118295", + "doi": "10.1016/j.watres.2022.118295", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hale, S. E. et al. Sorbent amendment as a remediation strategy to reduce PFAS mobility and leaching in a contaminated sandy soil from a Norwegian firefighting training facility. Chemosphere. 171, 9\u201318 (2017).", - "doi": "https://doi.org/10.1016/j.chemosphere.2016.12.057", + "doi": "10.1016/j.chemosphere.2016.12.057", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Barber, J. L. et al. Analysis of per-and polyfluorinated alkyl substances in air samples from Northwest Europe. J. Environ. Monit. 9, 530\u2013541 (2007).", - "doi": "https://doi.org/10.1039/b701417a", + "doi": "10.1039/b701417a", "pubmed_id": null, "title": null }, @@ -211,28 +211,28 @@ { "PMCID": null, "citation": "P\u00e9tr\u00e9, M. A. et al. Per-and polyfluoroalkyl substance (PFAS) transport from groundwater to streams near a PFAS manufacturing facility in North Carolina, USA. Environ. Sci. Tech. 55, 5848\u20135856 (2021).", - "doi": "https://doi.org/10.1021/acs.est.0c07978", + "doi": "10.1021/acs.est.0c07978", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ahrens, L., Norstr\u00f6m, K., Viktor, T., Cousins, A. P. & Josefsson, S. Stockholm Arlanda Airport as a source of per-and polyfluoroalkyl substances to water, sediment and fish. Chemosphere. 129, 33\u201338 (2015).", - "doi": "https://doi.org/10.1016/j.chemosphere.2014.03.136", + "doi": "10.1016/j.chemosphere.2014.03.136", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Adamson, D. T. et al. Mass-based, field-scale demonstration of PFAS retention within AFFF-associated source areas. Environ. Sci. Tech. 54, 15768\u201315777 (2020).", - "doi": "https://doi.org/10.1021/acs.est.0c04472", + "doi": "10.1021/acs.est.0c04472", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Quinnan, J. et al. Application of PFAS\u2010mobile lab to support adaptive characterization and flux\u2010based conceptual site models at AFFF releases. Remed. J. 31, 7\u201326 (2021).", - "doi": "https://doi.org/10.1002/rem.21680", + "doi": "10.1002/rem.21680", "pubmed_id": null, "title": null }, @@ -246,42 +246,42 @@ { "PMCID": null, "citation": "Hale, S. E., Canivet, B., Rundberget, T., Langberg, H. A. & Allan, I. J. Using passive samplers to track Per and Polyfluoroalkyl Substances (PFAS) emissions from the paper industry: laboratory calibration and field verification. Front. Env. Sci. 9, 621\u2013629 (2021).", - "doi": "https://doi.org/10.3389/fenvs.2021.796026", + "doi": "10.3389/fenvs.2021.796026", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Hu, X. C. et al. Detection of poly-and perfluoroalkyl substances (PFASs) in US drinking water linked to industrial sites, military fire training areas, and wastewater treatment plants. Environ. Sci. Tech. Let. 3, 344\u2013350 (2016).", - "doi": "https://doi.org/10.1021/acs.estlett.6b00260", + "doi": "10.1021/acs.estlett.6b00260", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integr. Environ. Assess. 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ebert, J. C. & Altman, R. B. Robust recognition of zinc binding sites in proteins. Protein Sci. 17, 54\u201365 (2008).", - "doi": "https://doi.org/10.1110/ps.073138508", + "doi": "10.1110/ps.073138508", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data. 3, 1\u20139 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -295,21 +295,21 @@ { "PMCID": null, "citation": "Zs\u00f3ka, \u00c1., Szer\u00e9nyi, Z. M., Sz\u00e9chy, A. & Kocsis, T. Greening due to environmental education? Environmental knowledge, attitudes, consumer behavior and everyday pro-environmental activities of Hungarian high school and university students. J. Clean. Prod. 48, 126\u2013138 (2013).", - "doi": "https://doi.org/10.1016/j.jclepro.2012.11.030", + "doi": "10.1016/j.jclepro.2012.11.030", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Guelfo, J. L. & Adamson, D. T. Evaluation of a national data set for insights into sources, composition, and concentrations of per-and polyfluoroalkyl substances (PFASs) in US drinking water. Environ, Poll. 236, 505\u2013513 (2018).", - "doi": "https://doi.org/10.1016/j.envpol.2018.01.066", + "doi": "10.1016/j.envpol.2018.01.066", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ohja, S., Thompson, P. T., Powell, C. D., Moselet, H. N. B. & Pennell, K. P. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null } @@ -374,8 +374,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 16, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -386,14 +386,14 @@ { "PMCID": null, "citation": "Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016).", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout, M. & Zielhuis, G. A.& Bredenoord, A. L. The FAIR guiding principles for data stewardship: fair enough? European journal of human genetics 26, 931\u2013936 (2018).", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, @@ -421,63 +421,63 @@ { "PMCID": null, "citation": "Protein Data Bank. the single global archive for 3D macromolecular structure data. Nucleic acids research 47, D520\u2013D528 (2019).", - "doi": "https://doi.org/10.1093/nar/gky949", + "doi": "10.1093/nar/gky949", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Clough, E. & Barrett, T. The gene expression omnibus database. Statistical genomics (pp. 93\u2013110. Humana Press, New York, NY, 2016). DOI: DOI 10, 978\u2013971.", - "doi": "https://doi.org/10.1007/978-1-4939-3578-9_5", + "doi": "10.1007/978-1-4939-3578-9_5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sud, M. et al. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research 44, D463\u2013D470 (2016).", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Sarkans, U. et al. From arrayexpress to biostudies. Nucleic Acids Research 49, D1502\u2013D1506 (2021).", - "doi": "https://doi.org/10.1093/nar/gkaa1062", + "doi": "10.1093/nar/gkaa1062", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Brazma, A. et al. Minimum information about a microarray experiment (MIAME)\u2014toward standards for microarray data. Nature genetics 29, 365\u2013371 (2001).", - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Edgar, R. & Barrett, T. NCBI GEO standards and services for microarray data. Nature biotechnology 24, 1471\u20131472 (2006).", - "doi": "https://doi.org/10.1038/nbt1206-1471", + "doi": "10.1038/nbt1206-1471", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter, A. & Moseley, H. N. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository. Metabolomics 14, 1\u20138 (2018).", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository. Metabolites 11, 163 (2021).", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell, C. D. & Moseley, H. N. The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv (2022).", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, @@ -498,21 +498,21 @@ { "PMCID": null, "citation": "Kinkade, D. & Shepherd, A. Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles. Geoscience Data Journal 9, 177\u2013186 (2022).", - "doi": "https://doi.org/10.1002/gdj3.120", + "doi": "10.1002/gdj3.120", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Pampel, H. et al. Making research data repositories visible: the re3data. org registry. PloS one 8, e78080 (2013).", - "doi": "https://doi.org/10.1371/journal.pone.0078080", + "doi": "10.1371/journal.pone.0078080", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Degbelo, A. FAIR geovisualizations: definitions, challenges, and the road ahead. International Journal of Geographical Information Science 36, 1059\u20131099 (2022).", - "doi": "https://doi.org/10.1080/13658816.2021.1983579", + "doi": "10.1080/13658816.2021.1983579", "pubmed_id": null, "title": null }, @@ -526,14 +526,14 @@ { "PMCID": null, "citation": "Sicilia, M.-A., Garc\u00eda-Barriocanal, E. & S\u00e1nchez-Alonso, S. Community curation in open dataset repositories: insights from Zenodo. Procedia Computer Science 106, 54\u201360 (2017).", - "doi": "https://doi.org/10.1016/j.procs.2017.03.009", + "doi": "10.1016/j.procs.2017.03.009", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Thelwall, M. & Kousha, K. Figshare: a universal repository for academic resource sharing? Online Information Review (2016).", - "doi": "https://doi.org/10.1108/OIR-06-2015-0190", + "doi": "10.1108/OIR-06-2015-0190", "pubmed_id": null, "title": null }, @@ -547,7 +547,7 @@ { "PMCID": null, "citation": "Ojha, S. et al. A geospatial and binomial logistic regression model to prioritize sampling for per\u2010and polyfluorinated alkyl substances in public water systems. Integrated environmental assessment and management 19, 163\u2013174 (2023).", - "doi": "https://doi.org/10.1002/ieam.4614", + "doi": "10.1002/ieam.4614", "pubmed_id": null, "title": null }, @@ -561,21 +561,21 @@ { "PMCID": null, "citation": "Thompson, P. T., Powell, C. D. & Moseley, H. N. Academic Tracker: Software for tracking and reporting publications associated with authors and grants. PloS one 17, e0277834 (2022).", - "doi": "https://doi.org/10.1371/journal.pone.0277834", + "doi": "10.1371/journal.pone.0277834", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reed, C. N. The open geospatial consortium and web services standards. In Geospatial Web Services: Advances in Information Interoperability, IGI Global: pp. 1\u201316 (2011).", - "doi": "https://doi.org/10.4018/978-1-60960-192-8.ch001", + "doi": "10.4018/978-1-60960-192-8.ch001", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Reichardt, M. Open geospatial consortium standards. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology 1\u20138 (2016).", - "doi": "https://doi.org/10.1002/9781118786352.wbieg0348", + "doi": "10.1002/9781118786352.wbieg0348", "pubmed_id": null, "title": null }, @@ -596,14 +596,14 @@ { "PMCID": null, "citation": "Ojha, S. et al. A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems-Dataset. Figshare https://doi.org/10.6084/m9.figshare.16560144 (2021).", - "doi": "https://doi.org/10.6084/m9.figshare.16560144", + "doi": "10.6084/m9.figshare.16560144", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Ojha, S., Moseley, H. & Powell, C. D., Pennell, K. G. & Thompson, P. T. A FAIR approach to detect and share PFAS hot-spot areas and water systems in Kentucky. Figshare https://doi.org/10.6084/m9.figshare.15218958 (2022).", - "doi": "https://doi.org/10.6084/m9.figshare.15218958", + "doi": "10.6084/m9.figshare.15218958", "pubmed_id": null, "title": null }, @@ -651,8 +651,8 @@ "keywords": null, "methods": null, "publication_date": { - "day": null, - "month": null, + "day": 24, + "month": 7, "year": 2023 }, "pubmed_id": null, @@ -670,35 +670,35 @@ { "PMCID": null, "citation": "Sud M, et al. Metabolomics workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res. 2016;44(D1):D463\u201370.", - "doi": "https://doi.org/10.1093/nar/gkv1042", + "doi": "10.1093/nar/gkv1042", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Smelter A, Moseley HN. A Python library for FAIRer access and deposition to the metabolomics workbench data repository. Metabolomics. 2018;14(5):1\u20138.", - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Wilkinson MD, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3(1):1\u20139.", - "doi": "https://doi.org/10.1038/sdata.2016.18", + "doi": "10.1038/sdata.2016.18", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Boeckhout M, et al. The FAIR guiding principles for data stewardship: fair enough? Eur J Hum Genet. 2018;26(7):931\u20136.", - "doi": "https://doi.org/10.1038/s41431-018-0160-0", + "doi": "10.1038/s41431-018-0160-0", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Powell CD, Moseley HN. The mwtab python library for RESTful access and enhanced quality control, deposition, and curation of the metabolomics workbench data repository. Metabolites. 2021;11(3):163.", - "doi": "https://doi.org/10.3390/metabo11030163", + "doi": "10.3390/metabo11030163", "pubmed_id": null, "title": null }, @@ -740,14 +740,14 @@ { "PMCID": null, "citation": "Metabolomics workbench mwTab and JSON formatted data files (as of Feb. 19th, 2022) Figshare repository. https://doi.org/10.6084/m9.figshare.19221159. Accessed 19 Feb 2022.", - "doi": "https://doi.org/10.6084/m9.figshare.19221159", + "doi": "10.6084/m9.figshare.19221159", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Haug K, et al. Global open data management in metabolomics. Curr Opin Chem Biol. 2017;36:58\u201363.", - "doi": "https://doi.org/10.1016/j.cbpa.2016.12.024", + "doi": "10.1016/j.cbpa.2016.12.024", "pubmed_id": null, "title": null }, @@ -761,7 +761,7 @@ { "PMCID": null, "citation": "Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A. ISA API: an open platform for interoperable life science experimental metadata. GigaScience. 2021;10(9):gia060.", - "doi": "https://doi.org/10.1093/gigascience/giab060", + "doi": "10.1093/gigascience/giab060", "pubmed_id": null, "title": null }, @@ -775,14 +775,14 @@ { "PMCID": null, "citation": "Joosten RP, et al. PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr. 2009;42(3):376\u201384.", - "doi": "https://doi.org/10.1107/S0021889809008784", + "doi": "10.1107/S0021889809008784", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Berman H, et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acid Res. 2007;35(suppl1):D301\u20133.", - "doi": "https://doi.org/10.1093/nar/gkl971", + "doi": "10.1093/nar/gkl971", "pubmed_id": null, "title": null } @@ -852,7 +852,7 @@ "methods": null, "publication_date": { "day": null, - "month": null, + "month": 6, "year": 2023 }, "pubmed_id": null, @@ -863,7 +863,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/533452a", + "doi": "10.1038/533452a", "pubmed_id": null, "title": null }, @@ -877,7 +877,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.17226/25116", + "doi": "10.17226/25116", "pubmed_id": null, "title": null }, @@ -905,21 +905,21 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/s41563-019-0332-5", + "doi": "10.1038/s41563-019-0332-5", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.cotox.2019.05.005", + "doi": "10.1016/j.cotox.2019.05.005", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfab157", + "doi": "10.1093/toxsci/kfab157", "pubmed_id": null, "title": null }, @@ -933,28 +933,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1371/journal.pbio.2006930", + "doi": "10.1371/journal.pbio.2006930", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/agriculture12020309", + "doi": "10.3390/agriculture12020309", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/nbt.1411", + "doi": "10.1038/nbt.1411", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng1201-365", + "doi": "10.1038/ng1201-365", "pubmed_id": null, "title": null }, @@ -982,28 +982,28 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/ng.1054", + "doi": "10.1038/ng.1054", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2008.0019", + "doi": "10.1089/omi.2008.0019", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1089/omi.2006.10.164", + "doi": "10.1089/omi.2006.10.164", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.4056/sigs.147362", + "doi": "10.4056/sigs.147362", "pubmed_id": null, "title": null }, @@ -1017,35 +1017,35 @@ { "PMCID": null, "citation": "Gamble M Goble C Klyne G Zhao J. 2012. MIM: A Minimum Information Model: A Minimum Information Model vocabulary and framework for Scientific Linked Data. In: 2012 IEEE 8th International Conference on E-Science. 8\u201312 October 2012. Chicago Illinois 1\u20138.", - "doi": "https://doi.org/10.1109/eScience.2012.6404489", + "doi": "10.1109/eScience.2012.6404489", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1289/EHP10092", + "doi": "10.1289/EHP10092", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1101/2021.09.27.461968", + "doi": "10.1101/2021.09.27.461968", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3389/frai.2020.00031", + "doi": "10.3389/frai.2020.00031", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfm090", + "doi": "10.1093/toxsci/kfm090", "pubmed_id": null, "title": null }, @@ -1073,7 +1073,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.comtox.2019.100096", + "doi": "10.1016/j.comtox.2019.100096", "pubmed_id": null, "title": null }, @@ -1087,7 +1087,7 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkz1019", + "doi": "10.1093/nar/gkz1019", "pubmed_id": null, "title": null }, @@ -1101,119 +1101,119 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.envint.2022.107243", + "doi": "10.1016/j.envint.2022.107243", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gkm755", + "doi": "10.1093/nar/gkm755", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.reprotox.2019.07.012", + "doi": "10.1016/j.reprotox.2019.07.012", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1053/j.seminoncol.2019.09.002", + "doi": "10.1053/j.seminoncol.2019.09.002", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1182/blood-2017-03-735654", + "doi": "10.1182/blood-2017-03-735654", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1002/cpt.666", + "doi": "10.1002/cpt.666", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1515/reveh-2019-0089", + "doi": "10.1515/reveh-2019-0089", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1021/acs.est.1c08383", + "doi": "10.1021/acs.est.1c08383", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1038/d41586-022-02820-7", + "doi": "10.1038/d41586-022-02820-7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/2041-1480-4-36", + "doi": "10.1186/2041-1480-4-36", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": "Law M, Shaw DR. 2018. Mouse Genome Informatics (MGI) is the international resource for information on the laboratory mouse. In: Eukaryotic Genomic Databases: Methods and Protocols. Kollmar M, ed. New York, NY: Springer New York, 141\u2013161.", - "doi": "https://doi.org/10.1007/978-1-4939-7737-6_7", + "doi": "10.1007/978-1-4939-7737-6_7", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1186/s12917-020-02451-y", + "doi": "10.1186/s12917-020-02451-y", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.3390/ijerph18178985", + "doi": "10.3390/ijerph18178985", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/toxsci/kfq355", + "doi": "10.1093/toxsci/kfq355", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1016/j.toxlet.2019.04.003", + "doi": "10.1016/j.toxlet.2019.04.003", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.26434/chemrxiv-2022-bt3f6", + "doi": "10.26434/chemrxiv-2022-bt3f6", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - 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The Metabolomics Workbench File Status Website: A Metadata Repository Promoting FAIR Principles of Metabolomics Data. bioRxiv.", - "doi": "https://doi.org/10.1101/2022.03.04.483070", + "doi": "10.1101/2022.03.04.483070", "pubmed_id": null, "title": null }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/nar/gks1004", + "doi": "10.1093/nar/gks1004", "pubmed_id": null, "title": "MetaboLights\u2014An open-access general-purpose repository for metabolomics studies and associated meta-data" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1093/database/bat029", + "doi": "10.1093/database/bat029", "pubmed_id": null, "title": "The MetaboLights repository: Curation challenges in metabolomics" }, @@ -1872,7 +1872,7 @@ { "PMCID": null, "citation": "Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., and Vrgo\u010d, D. (2016, January 11\u201315). Foundations of JSON schema. Proceedings of the 25th International Conference on World Wide Web, Montreal, QC, Canada.", - "doi": "https://doi.org/10.1145/2872427.2883029", + "doi": "10.1145/2872427.2883029", "pubmed_id": null, "title": null }, @@ -1914,14 +1914,14 @@ { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1109/MCSE.2010.118", + "doi": "10.1109/MCSE.2010.118", "pubmed_id": null, "title": "Cython: The best of both worlds" }, { "PMCID": null, "citation": null, - "doi": "https://doi.org/10.1007/s11306-018-1356-6", + "doi": "10.1007/s11306-018-1356-6", "pubmed_id": null, "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository" }, diff --git a/tests/testing_files/tokenized_citations_missing_ref_line.json b/tests/testing_files/tokenized_citations_missing_ref_line.json new file mode 100644 index 0000000..927fd58 --- /dev/null +++ b/tests/testing_files/tokenized_citations_missing_ref_line.json @@ -0,0 +1,3471 @@ +[ + { + "DOI": "10.3390/metabo11110740", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Flight R, Moseley H.\n \n Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue.\n Metabolites. 2021 October; 11(11):740-. doi: 10.3390/metabo11110740.", + "title": "Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue." + }, + { + "DOI": "10.3390/metabo11070431", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Jin" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Jin H, Moseley H.\n \n Hierarchical Harmonization of Atom-Resolved Metabolic Reactions across Metabolic Databases.\n Metabolites. 2021 June; 11(7):431-. doi: 10.3390/metabo11070431.", + "title": "Hierarchical Harmonization of Atom-Resolved Metabolic Reactions across Metabolic Databases." + }, + { + "DOI": "10.1101/2021.06.01.446673", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Jin" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Jin H, Moseley H.\n Hierarchical Harmonization of Atom-Resolved Metabolic Reactions Across Metabolic Databases. [preprint]. 2021 June. doi: 10.1101/2021.06.01.446673.", + "title": "Hierarchical Harmonization of Atom-Resolved Metabolic Reactions Across Metabolic Databases." + }, + { + "DOI": "10.1093/bioinformatics/btaa957", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Liu" + }, + { + "initials": "J", + "last": "Liu" + }, + { + "initials": "Y", + "last": "Xie" + }, + { + "initials": "T", + "last": "Zhai" + }, + { + "initials": "E", + "last": "Hinderer" + }, + { + "initials": "A", + "last": "Stromberg" + }, + { + "initials": "N", + "last": "Vanderford" + }, + { + "initials": "J", + "last": "Kolesar" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "L", + "last": "Chen" + }, + { + "initials": "C", + "last": "Liu" + }, + { + "initials": "C", + "last": "Wang" + } + ], + "pub_dict_key": "", + "reference_line": "Liu S, Liu J, Xie Y, Zhai T, Hinderer E, Stromberg A, Vanderford N, Kolesar J, Moseley H, Chen L, Liu C, Wang C.\n \n MEScan: a powerful statistical framework for genome-scale mutual exclusivity analysis of cancer mutations.\n Bioinformatics. 2021 May; 37(9):1189-1197. doi: 10.1093/bioinformatics/btaa957.", + "title": "MEScan: a powerful statistical framework for genome-scale mutual exclusivity analysis of cancer mutations." + }, + { + "DOI": "10.1101/2021.03.16.21253733", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Flight R, Lane A, Moseley H.\n Untargeted lipidomics of non-small cell lung carcinoma shows differentially abundant lipid classes in cancer vs non-cancer tissue. [preprint]. 2021 March. doi: 10.1101/2021.03.16.21253733.", + "title": "Untargeted lipidomics of non-small cell lung carcinoma shows differentially abundant lipid classes in cancer vs non-cancer tissue." + }, + { + "DOI": "10.3390/metabo11030163", + "PMID": "", + "authors": [ + { + "initials": "C", + "last": "Powell" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Powell C, Moseley H.\n \n The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository.\n Metabolites. 2021 March; 11(3):163-. doi: 10.3390/metabo11030163.", + "title": "The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository." + }, + { + "DOI": "10.3390/metabo11030163", + "PMID": "33808985", + "authors": [ + { + "initials": "CD", + "last": "Powell" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Powell CD, Moseley HNB.\n \n The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository.\n Metabolites.\n \n \n 2021 Mar 12;11(3). doi: 10.3390/metabo11030163. PubMed PMID:\n 33808985; PubMed Central PMCID:\n PMC8000456.", + "title": "The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository." + }, + { + "DOI": "10.1016/j.bbadis.2020.165883", + "PMID": "32592935", + "authors": [ + { + "initials": "Y", + "last": "Zhong" + }, + { + "initials": "K", + "last": "Mohan" + }, + { + "initials": "J", + "last": "Liu" + }, + { + "initials": "A", + "last": "Al-Attar" + }, + { + "initials": "P", + "last": "Lin" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "Q", + "last": "Sun" + }, + { + "initials": "MO", + "last": "Warmoes" + }, + { + "initials": "RR", + "last": "Deshpande" + }, + { + "initials": "H", + "last": "Liu" + }, + { + "initials": "KS", + "last": "Jung" + }, + { + "initials": "MI", + "last": "Mitov" + }, + { + "initials": "N", + "last": "Lin" + }, + { + "initials": "DA", + "last": "Butterfield" + }, + { + "initials": "S", + "last": "Lu" + }, + { + "initials": "J", + "last": "Liu" + }, + { + "initials": "HNB", + "last": "Moseley" + }, + { + "initials": "TWM", + "last": "Fan" + }, + { + "initials": "ME", + "last": "Kleinman" + }, + { + "initials": "QJ", + "last": "Wang" + } + ], + "pub_dict_key": "", + "reference_line": "Zhong Y, Mohan K, Liu J, Al-Attar A, Lin P, Flight RM, Sun Q, Warmoes MO, Deshpande RR, Liu H, Jung KS, Mitov MI, Lin N, Butterfield DA, Lu S, Liu J, Moseley HNB, Fan TWM, Kleinman ME, Wang QJ.\n \n Loss of CLN3, the gene mutated in juvenile neuronal ceroid lipofuscinosis, leads to metabolic impairment and autophagy induction in retinal pigment epithelium.\n Biochim Biophys Acta Mol Basis Dis.\n \n \n 2020 Oct 1;1866(10):165883. doi: 10.1016/j.bbadis.2020.165883. Epub 2020 Jun 25. PubMed PMID:\n 32592935; NIHMSID:NIHMS1607350.", + "title": "Loss of CLN3, the gene mutated in juvenile neuronal ceroid lipofuscinosis, leads to metabolic impairment and autophagy induction in retinal pigment epithelium." + }, + { + "DOI": "10.3390/metabo10090368", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Jin" + }, + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Jin H, Mitchell J, Moseley H.\n \n Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases.\n Metabolites. 2020 September; 10(9):368-. doi: 10.3390/metabo10090368.", + "title": "Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases." + }, + { + "DOI": "10.1371/journal.pone.0236894", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Moseley H.\n \n A chemical interpretation of protein electron density maps in the worldwide protein data bank.\n PLOS ONE. 2020-8-; 15(8):e0236894-. doi: 10.1371/journal.pone.0236894.", + "title": "A chemical interpretation of protein electron density maps in the worldwide protein data bank." + }, + { + "DOI": "10.1101/2020.06.19.161877", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Jin" + }, + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Jin H, Mitchell J, Moseley H.\n Atom Identifiers Generated by a Graph Coloring Method Enable Compound Harmonization Across Metabolic Databases. [preprint]. 2020 June. doi: 10.1101/2020.06.19.161877.", + "title": "Atom Identifiers Generated by a Graph Coloring Method Enable Compound Harmonization Across Metabolic Databases." + }, + { + "DOI": "10.1371/journal.pone.0233311", + "PMID": "", + "authors": [ + { + "initials": "E", + "last": "Hinderer" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Hinderer E, Moseley H.\n \n GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts.\n PLOS ONE. 2020-6-; 15(6):e0233311-. doi: 10.1371/journal.pone.0233311.", + "title": "GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts." + }, + { + "DOI": "10.1093/bioinformatics/btaa106", + "PMID": "", + "authors": [ + { + "initials": "R", + "last": "Abeysinghe" + }, + { + "initials": "E", + "last": "Hinderer" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "L", + "last": "Cui" + } + ], + "pub_dict_key": "", + "reference_line": "Abeysinghe R, Hinderer E, Moseley H, Cui L.\n \n SSIF: Subsumption-based Sub-term Inference Framework to audit Gene Ontology.\n Bioinformatics. 2020 May; 36(10):3207-3214. doi: 10.1093/bioinformatics/btaa106.", + "title": "SSIF: Subsumption-based Sub-term Inference Framework to audit Gene Ontology." + }, + { + "DOI": "10.31219/osf.io/z8wvq", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H.\n Current Evidence Supporting the Use of Orally Administered Zinc in the Treatment of COVID-19. [preprint]. 2020 April. doi: 10.31219/osf.io/z8wvq.", + "title": "Current Evidence Supporting the Use of Orally Administered Zinc in the Treatment of COVID-19." + }, + { + "DOI": "10.1186/s12864-020-6681-2", + "PMID": "", + "authors": [ + { + "initials": "C", + "last": "Powell" + }, + { + "initials": "D", + "last": "Kirchoff" + }, + { + "initials": "J", + "last": "DeRouchey" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Powell C, Kirchoff D, DeRouchey J, Moseley H.\n \n Entropy based analysis of vertebrate sperm protamines sequences: evidence of potential dityrosine and cysteine-tyrosine cross-linking in sperm protamines.\n BMC Genomics. 2020 April; 21(1):-. doi: 10.1186/s12864-020-6681-2.", + "title": "Entropy based analysis of vertebrate sperm protamines sequences: evidence of potential dityrosine and cysteine-tyrosine cross-linking in sperm protamines." + }, + { + "DOI": "10.3390/metabo10030122", + "PMID": "32214009", + "authors": [ + { + "initials": "JM", + "last": "Mitchell" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell JM, Flight RM, Moseley HNB.\n \n Deriving Lipid Classification Based on Molecular Formulas.\n Metabolites.\n \n \n 2020 Mar 24;10(3). doi: 10.3390/metabo10030122. PubMed PMID:\n 32214009; PubMed Central PMCID:\n PMC7143220.", + "title": "Deriving Lipid Classification Based on Molecular Formulas." + }, + { + "DOI": "10.3390/metabo10030122", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Flight R, Moseley H.\n \n Deriving Lipid Classification Based on Molecular Formulas.\n Metabolites. 2020 March; 10(3):122-. doi: 10.3390/metabo10030122.", + "title": "Deriving Lipid Classification Based on Molecular Formulas." + }, + { + "DOI": "10.3390/metabo10030118", + "PMID": "32245221", + "authors": [ + { + "initials": "H", + "last": "Jin" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Jin H, Moseley HNB.\n \n Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues.\n Metabolites.\n \n \n 2020 Mar 21;10(3). doi: 10.3390/metabo10030118. PubMed PMID:\n 32245221; PubMed Central PMCID:\n PMC7143054.", + "title": "Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues." + }, + { + "DOI": "10.3390/metabo10030118", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Jin" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Jin H, Moseley H.\n \n Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues.\n Metabolites. 2020 March; 10(3):118-. doi: 10.3390/metabo10030118.", + "title": "Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues." + }, + { + "DOI": "10.1101/845180", + "PMID": "", + "authors": [ + { + "initials": "C", + "last": "Powell" + }, + { + "initials": "D", + "last": "Kirchhoff" + }, + { + "initials": "J", + "last": "DeRouchey" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Powell C, Kirchhoff D, DeRouchey J, Moseley H.\n Entropy-Based Analysis of Vertebrate Sperm Protamine Sequences: Evidence of Dityrosine and Cysteine-Tyrosine Cross-Linking in Sperm Protamines. [preprint]. 2019 November. doi: 10.1101/845180.", + "title": "Entropy-Based Analysis of Vertebrate Sperm Protamine Sequences: Evidence of Dityrosine and Cysteine-Tyrosine Cross-Linking in Sperm Protamines." + }, + { + "DOI": "10.1186/s12859-019-3096-7", + "PMID": "31660850", + "authors": [ + { + "initials": "H", + "last": "Jin" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Jin H, Moseley HNB.\n \n Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues.\n BMC Bioinformatics.\n \n \n 2019 Oct 28;20(1):524. doi: 10.1186/s12859-019-3096-7. PubMed PMID:\n 31660850; PubMed Central PMCID:\n PMC6816163.", + "title": "Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues." + }, + { + "DOI": "10.1186/s12859-019-3096-7", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Jin" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Jin H, Moseley H.\n \n Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues.\n BMC Bioinformatics. 2019 October; 20(1):-. doi: 10.1186/s12859-019-3096-7.", + "title": "Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues." + }, + { + "DOI": "10.3390/molecules24173179", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Moseley H.\n \n Finding High-Quality Metal Ion-Centric Regions Across the Worldwide Protein Data Bank.\n Molecules. 2019 September; 24(17):3179-. doi: 10.3390/molecules24173179.", + "title": "Finding High-Quality Metal Ion-Centric Regions Across the Worldwide Protein Data Bank." + }, + { + "DOI": "10.1371/journal.pone.0220728", + "PMID": "", + "authors": [ + { + "initials": "E", + "last": "Hinderer" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "R", + "last": "Dubey" + }, + { + "initials": "J", + "last": "MacLeod" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Hinderer E, Flight R, Dubey R, MacLeod J, Moseley H.\n \n Advances in gene ontology utilization improve statistical power of annotation enrichment.\n PLOS ONE. 2019-8-; 14(8):e0220728-. doi: 10.1371/journal.pone.0220728.", + "title": "Advances in gene ontology utilization improve statistical power of annotation enrichment." + }, + { + "DOI": "10.1021/acs.analchem.9b00748", + "PMID": "31260262", + "authors": [ + { + "initials": "JM", + "last": "Mitchell" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell JM, Flight RM, Moseley HNB.\n \n Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra.\n Anal Chem.\n \n \n 2019 Jul 16;91(14):8933-8940. doi: 10.1021/acs.analchem.9b00748. Epub 2019 Jul 1. PubMed PMID:\n 31260262.", + "title": "Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra." + }, + { + "DOI": "10.1021/acs.analchem.9b00748", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Flight R, Moseley H.\n \n Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra.\n Analytical Chemistry. 2019 June; 91(14):8933-8940. doi: 10.1021/acs.analchem.9b00748.", + "title": "Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra." + }, + { + "DOI": "10.1177/1934578x19849142", + "PMID": "", + "authors": [ + { + "initials": "X", + "last": "Chen" + }, + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Chen X, Smelter A, Moseley HN.\n \n BaMORC: A Software Package for Accurate and Robust 13C Reference Correction of Protein NMR Spectra.\n Natural Products Communication. 2019 May; 14. doi: 10.1177/1934578X19849142.", + "title": "BaMORC: A Software Package for Accurate and Robust 13C Reference Correction of Protein NMR Spectra." + }, + { + "DOI": "10.26434/chemrxiv.7609205", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Mitchell J, Flight R.\n Small Molecule Isotope Resolved Formula Enumeration: a Methodology for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra. [preprint]. 2019-5-. doi: 10.26434/chemrxiv.7609205.", + "title": "Small Molecule Isotope Resolved Formula Enumeration: a Methodology for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra." + }, + { + "DOI": "10.26434/chemrxiv.7609205.v3", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Mitchell J, Flight R.\n Small Molecule Isotope Resolved Formula Enumeration: a Methodology for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra. [preprint]. 2019 May. doi: 10.26434/chemrxiv.7609205.v3.", + "title": "Small Molecule Isotope Resolved Formula Enumeration: a Methodology for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra." + }, + { + "DOI": "10.26434/chemrxiv.7609205.v2", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Mitchell J, Flight R.\n Small Molecule Isotope Resolved Formula Enumeration: a Methodology for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra. [preprint]. 2019 May. doi: 10.26434/chemrxiv.7609205.v2.", + "title": "Small Molecule Isotope Resolved Formula Enumeration: a Methodology for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra." + }, + { + "DOI": "10.1177/1176935119843507", + "PMID": "31105425", + "authors": [ + { + "initials": "MK", + "last": "Gober" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "J", + "last": "Lambert" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "A", + "last": "Stromberg" + }, + { + "initials": "EP", + "last": "Black" + } + ], + "pub_dict_key": "", + "reference_line": "Gober MK, Flight RM, Lambert J, Moseley H, Stromberg A, Black EP.\n \n Deregulation of a Network of mRNA and miRNA Genes Reveals That CK2 and MEK Inhibitors May Synergize to Induce Apoptosis KRAS-Active NSCLC.\n Cancer Inform.\n \n \n 2019;18:1176935119843507. doi: 10.1177/1176935119843507. eCollection 2019. PubMed PMID:\n 31105425; PubMed Central PMCID:\n PMC6509975.", + "title": "Deregulation of a Network of mRNA and miRNA Genes Reveals That CK2 and MEK Inhibitors May Synergize to Induce Apoptosis KRAS-Active NSCLC." + }, + { + "DOI": "10.1177/1176935119843507", + "PMID": "", + "authors": [ + { + "initials": "M", + "last": "Gober" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "J", + "last": "Lambert" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "A", + "last": "Stromberg" + }, + { + "initials": "E", + "last": "Black" + } + ], + "pub_dict_key": "", + "reference_line": "Gober M, Flight R, Lambert J, Moseley H, Stromberg A, Black E.\n \n Deregulation of a Network of mRNA and miRNA Genes Reveals That CK2 and MEK Inhibitors May Synergize to Induce Apoptosis KRAS-Active NSCLC.\n Cancer Informatics. 2019 May; 18:117693511984350-. doi: 10.1177/1176935119843507.", + "title": "Deregulation of a Network of mRNA and miRNA Genes Reveals That CK2 and MEK Inhibitors May Synergize to Induce Apoptosis KRAS-Active NSCLC." + }, + { + "DOI": "10.1101/619809", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Moseley H.\n Finding high-quality metal ion-centric regions across the worldwide Protein Data Bank. [preprint]. 2019 April. doi: 10.1101/619809.", + "title": "Finding high-quality metal ion-centric regions across the worldwide Protein Data Bank." + }, + { + "DOI": "10.1101/613109", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Moseley H.\n A chemical interpretation of protein electron density maps in the worldwide protein data bank. [preprint]. 2019 April. doi: 10.1101/613109.", + "title": "A chemical interpretation of protein electron density maps in the worldwide protein data bank." + }, + { + "DOI": "10.21203/rs.2.525/v1", + "PMID": "", + "authors": [ + { + "initials": "E", + "last": "Hinderer" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Hinderer E, Moseley H.\n GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts. [preprint]. 2019 March. doi: 10.21203/rs.2.525/v1.", + "title": "GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts." + }, + { + "DOI": "10.1101/572883", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Moseley H.\n Deriving Accurate Lipid Classification based on Molecular Formula. [preprint]. 2019 March. doi: 10.1101/572883.", + "title": "Deriving Accurate Lipid Classification based on Molecular Formula." + }, + { + "DOI": "10.1158/1055-9965.epi-17-0984", + "PMID": "30377206", + "authors": [ + { + "initials": "J", + "last": "Liu" + }, + { + "initials": "T", + "last": "Murali" + }, + { + "initials": "T", + "last": "Yu" + }, + { + "initials": "C", + "last": "Liu" + }, + { + "initials": "TA", + "last": "Sivakumaran" + }, + { + "initials": "HNB", + "last": "Moseley" + }, + { + "initials": "IB", + "last": "Zhulin" + }, + { + "initials": "HL", + "last": "Weiss" + }, + { + "initials": "EB", + "last": "Durbin" + }, + { + "initials": "SR", + "last": "Ellingson" + }, + { + "initials": "J", + "last": "Liu" + }, + { + "initials": "B", + "last": "Huang" + }, + { + "initials": "BJ", + "last": "Hallahan" + }, + { + "initials": "CM", + "last": "Horbinski" + }, + { + "initials": "K", + "last": "Hodges" + }, + { + "initials": "DL", + "last": "Napier" + }, + { + "initials": "T", + "last": "Bocklage" + }, + { + "initials": "J", + "last": "Mueller" + }, + { + "initials": "NL", + "last": "Vanderford" + }, + { + "initials": "DW", + "last": "Fardo" + }, + { + "initials": "C", + "last": "Wang" + }, + { + "initials": "SM", + "last": "Arnold" + } + ], + "pub_dict_key": "", + "reference_line": "Liu J, Murali T, Yu T, Liu C, Sivakumaran TA, Moseley HNB, Zhulin IB, Weiss HL, Durbin EB, Ellingson SR, Liu J, Huang B, Hallahan BJ, Horbinski CM, Hodges K, Napier DL, Bocklage T, Mueller J, Vanderford NL, Fardo DW, Wang C, Arnold SM.\n \n Characterization of Squamous Cell Lung Cancers from Appalachian Kentucky.\n Cancer Epidemiol Biomarkers Prev.\n \n \n 2019 Feb;28(2):348-356. doi: 10.1158/1055-9965.EPI-17-0984. Epub 2018 Oct 30. PubMed PMID:\n 30377206; PubMed Central PMCID:\n PMC6363884.", + "title": "Characterization of Squamous Cell Lung Cancers from Appalachian Kentucky." + }, + { + "DOI": "10.1158/1055-9965.epi-17-0984", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Liu" + }, + { + "initials": "T", + "last": "Murali" + }, + { + "initials": "T", + "last": "Yu" + }, + { + "initials": "C", + "last": "Liu" + }, + { + "initials": "T", + "last": "Sivakumaran" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "I", + "last": "Zhulin" + }, + { + "initials": "H", + "last": "Weiss" + }, + { + "initials": "E", + "last": "Durbin" + }, + { + "initials": "S", + "last": "Ellingson" + }, + { + "initials": "J", + "last": "Liu" + }, + { + "initials": "B", + "last": "Huang" + }, + { + "initials": "B", + "last": "Hallahan" + }, + { + "initials": "C", + "last": "Horbinski" + }, + { + "initials": "K", + "last": "Hodges" + }, + { + "initials": "D", + "last": "Napier" + }, + { + "initials": "T", + "last": "Bocklage" + }, + { + "initials": "J", + "last": "Mueller" + }, + { + "initials": "N", + "last": "Vanderford" + }, + { + "initials": "D", + "last": "Fardo" + }, + { + "initials": "C", + "last": "Wang" + }, + { + "initials": "S", + "last": "Arnold" + } + ], + "pub_dict_key": "", + "reference_line": "Liu J, Murali T, Yu T, Liu C, Sivakumaran T, Moseley H, Zhulin I, Weiss H, Durbin E, Ellingson S, Liu J, Huang B, Hallahan B, Horbinski C, Hodges K, Napier D, Bocklage T, Mueller J, Vanderford N, Fardo D, Wang C, Arnold S.\n \n Characterization of Squamous Cell Lung Cancers from Appalachian Kentucky.\n Cancer Epidemiology Biomarkers & Prevention. 2019 February; 28(2):348-356. doi: 10.1158/1055-9965.EPI-17-0984.", + "title": "Characterization of Squamous Cell Lung Cancers from Appalachian Kentucky." + }, + { + "DOI": "10.26434/chemrxiv.7609205.v1", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Mitchell J, Flight R.\n Small Molecule Isotope Resolved Formula Enumerator: a Tool for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra. [preprint]. 2019 January. doi: 10.26434/chemrxiv.7609205.v1.", + "title": "Small Molecule Isotope Resolved Formula Enumerator: a Tool for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra." + }, + { + "DOI": "10.1007/s10858-018-0202-5", + "PMID": "30097912", + "authors": [ + { + "initials": "X", + "last": "Chen" + }, + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Chen X, Smelter A, Moseley HNB.\n \n Automatic 13C chemical shift reference correction for unassigned protein NMR spectra.\n J Biomol NMR.\n \n \n 2018 Oct;72(1-2):11-28. doi: 10.1007/s10858-018-0202-5. Epub 2018 Aug 10. PubMed PMID:\n 30097912; PubMed Central PMCID:\n PMC6209040.", + "title": "Automatic 13C chemical shift reference correction for unassigned protein NMR spectra." + }, + { + "DOI": "10.1101/419085", + "PMID": "", + "authors": [ + { + "initials": "E", + "last": "Hinderer" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "R", + "last": "Dubey" + }, + { + "initials": "J", + "last": "MacLeod" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Hinderer E, Flight R, Dubey R, MacLeod J, Moseley H.\n Advances in Gene Ontology Utilization Improve Statistical Power of Annotation Enrichment. [preprint]. 2018 September. doi: 10.1101/419085.", + "title": "Advances in Gene Ontology Utilization Improve Statistical Power of Annotation Enrichment." + }, + { + "DOI": "10.1007/s11306-018-1426-9", + "PMID": "30830442", + "authors": [ + { + "initials": "JM", + "last": "Mitchell" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "QJ", + "last": "Wang" + }, + { + "initials": "RM", + "last": "Higashi" + }, + { + "initials": "TW", + "last": "Fan" + }, + { + "initials": "AN", + "last": "Lane" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell JM, Flight RM, Wang QJ, Higashi RM, Fan TW, Lane AN, Moseley HNB.\n \n New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis.\n Metabolomics.\n \n \n 2018 Sep 17;14(10):125. doi: 10.1007/s11306-018-1426-9. PubMed PMID:\n 30830442; PubMed Central PMCID:\n PMC6153687.", + "title": "New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis." + }, + { + "DOI": "10.1007/s11306-018-1426-9", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "Q", + "last": "Wang" + }, + { + "initials": "R", + "last": "Higashi" + }, + { + "initials": "T", + "last": "Fan" + }, + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Flight R, Wang Q, Higashi R, Fan T, Lane A, Moseley H.\n \n New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis.\n Metabolomics. 2018-9-; 14(10):-. doi: 10.1007/s11306-018-1426-9.", + "title": "New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis." + }, + { + "DOI": "10.1007/s10858-018-0202-5", + "PMID": "", + "authors": [ + { + "initials": "X", + "last": "Chen" + }, + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Chen X, Smelter A, Moseley H.\n \n Automatic 13C chemical shift reference correction for unassigned protein NMR spectra.\n Journal of Biomolecular NMR. 2018-8-; 72(1-2):11-28. doi: 10.1007/s10858-018-0202-5.", + "title": "Automatic 13C chemical shift reference correction for unassigned protein NMR spectra." + }, + { + "DOI": "10.18632/oncotarget.25361", + "PMID": "29872506", + "authors": [ + { + "initials": "YY", + "last": "Zaytseva" + }, + { + "initials": "PG", + "last": "Rychahou" + }, + { + "initials": "AT", + "last": "Le" + }, + { + "initials": "TL", + "last": "Scott" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "JT", + "last": "Kim" + }, + { + "initials": "J", + "last": "Harris" + }, + { + "initials": "J", + "last": "Liu" + }, + { + "initials": "C", + "last": "Wang" + }, + { + "initials": "AJ", + "last": "Morris" + }, + { + "initials": "TA", + "last": "Sivakumaran" + }, + { + "initials": "T", + "last": "Fan" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "T", + "last": "Gao" + }, + { + "initials": "EY", + "last": "Lee" + }, + { + "initials": "HL", + "last": "Weiss" + }, + { + "initials": "TS", + "last": "Heuer" + }, + { + "initials": "G", + "last": "Kemble" + }, + { + "initials": "M", + "last": "Evers" + } + ], + "pub_dict_key": "", + "reference_line": "Zaytseva YY, Rychahou PG, Le AT, Scott TL, Flight RM, Kim JT, Harris J, Liu J, Wang C, Morris AJ, Sivakumaran TA, Fan T, Moseley H, Gao T, Lee EY, Weiss HL, Heuer TS, Kemble G, Evers M.\n \n Preclinical evaluation of novel fatty acid synthase inhibitors in primary colorectal cancer cells and a patient-derived xenograft model of colorectal cancer.\n Oncotarget.\n \n \n 2018 May 15;9(37):24787-24800. doi: 10.18632/oncotarget.25361. eCollection 2018 May 15. PubMed PMID:\n 29872506; PubMed Central PMCID:\n PMC5973868.", + "title": "Preclinical evaluation of novel fatty acid synthase inhibitors in primary colorectal cancer cells and a patient-derived xenograft model of colorectal cancer." + }, + { + "DOI": "10.1101/306936", + "PMID": "", + "authors": [ + { + "initials": "E", + "last": "Hinderer" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Hinderer E, Moseley H.\n GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts. [preprint]. 2018 April. doi: 10.1101/306936.", + "title": "GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts." + }, + { + "DOI": "10.1007/s11306-018-1356-6", + "PMID": "29706851", + "authors": [ + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Smelter A, Moseley HNB.\n \n A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository.\n Metabolomics.\n \n \n 2018;14(5):64. doi: 10.1007/s11306-018-1356-6. Epub 2018 Apr 20. PubMed PMID:\n 29706851; PubMed Central PMCID:\n PMC5910482.", + "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository." + }, + { + "DOI": "10.1007/s11306-018-1356-6", + "PMID": "", + "authors": [ + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Smelter A, Moseley H.\n \n A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository.\n Metabolomics. 2018-4-; 14(5):-. doi: 10.1007/s11306-018-1356-6.", + "title": "A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository." + }, + { + "DOI": "10.1109/bibm.2018.8621511", + "PMID": "", + "authors": [ + { + "initials": "R", + "last": "Abeysinghe" + }, + { + "initials": "F", + "last": "Zheng" + }, + { + "initials": "III", + "last": "Hinderer" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "L", + "last": "Cui" + } + ], + "pub_dict_key": "", + "reference_line": "Abeysinghe R, Zheng F, Hinderer III EW, Moseley HN, Cui L.\n \n A Lexical Approach to Identifying Subtype Inconsistencies in Biomedical Terminologies.\n Quality Assurance of Biological and Biomedical Ontologies and Terminologies Workshop -- Bioinformatics and Biomedicine (BIBM), 2018 IEEE International Conference. 2018; :1982. doi: 10.1109/BIBM.2018.8621511.", + "title": "A Lexical Approach to Identifying Subtype Inconsistencies in Biomedical Terminologies." + }, + { + "DOI": "10.1101/191205", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "Q", + "last": "Wang" + }, + { + "initials": "W", + "last": "Kang" + }, + { + "initials": "R", + "last": "Higashi" + }, + { + "initials": "T", + "last": "Fan" + }, + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Flight R, Wang Q, Kang W, Higashi R, Fan T, Lane A, Moseley H.\n High Peak Density Artifacts in Fourier Transform Mass Spectra and their Effects on Data Analysis. [preprint]. 2017 September. doi: 10.1101/191205.", + "title": "High Peak Density Artifacts in Fourier Transform Mass Spectra and their Effects on Data Analysis." + }, + { + "DOI": "10.1007/s10858-017-0126-5", + "PMID": "28815397", + "authors": [ + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "EC", + "last": "Rouchka" + }, + { + "initials": "HNB", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Smelter A, Rouchka EC, Moseley HNB.\n \n Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping.\n J Biomol NMR.\n \n \n 2017 Aug;68(4):281-296. doi: 10.1007/s10858-017-0126-5. Epub 2017 Aug 16. PubMed PMID:\n 28815397; PubMed Central PMCID:\n PMC5587626.", + "title": "Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping." + }, + { + "DOI": "10.1007/s10858-017-0126-5", + "PMID": "", + "authors": [ + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "E", + "last": "Rouchka" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Smelter A, Rouchka E, Moseley H.\n \n Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping.\n Journal of Biomolecular NMR. 2017-8-; 68(4):281-296. doi: 10.1007/s10858-017-0126-5.", + "title": "Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping." + }, + { + "DOI": "10.1002/prot.25263", + "PMID": "28168746", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "EC", + "last": "Rouchka" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight RM, Rouchka EC, Moseley HN.\n \n Perspectives and expectations in structural bioinformatics of metalloproteins.\n Proteins.\n \n \n 2017 May;85(5):938-944. doi: 10.1002/prot.25263. Epub 2017 Mar 15. PubMed PMID:\n 28168746; PubMed Central PMCID:\n PMC5389925.", + "title": "Perspectives and expectations in structural bioinformatics of metalloproteins." + }, + { + "DOI": "10.1002/prot.25257", + "PMID": "28142195", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "EC", + "last": "Rouchka" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight RM, Rouchka EC, Moseley HN.\n \n Aberrant coordination geometries discovered in the most abundant metalloproteins.\n Proteins.\n \n \n 2017 May;85(5):885-907. doi: 10.1002/prot.25257. Epub 2017 Mar 7. PubMed PMID:\n 28142195; PubMed Central PMCID:\n PMC5389913.", + "title": "Aberrant coordination geometries discovered in the most abundant metalloproteins." + }, + { + "DOI": "10.1002/prot.25126", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "E", + "last": "Rouchka" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight R, Rouchka E, Moseley H.\n \n Cover Image, Volume 85, Issue 5.\n Proteins: Structure, Function, and Bioinformatics. 2017 May; 85(5):C1-C1. doi: 10.1002/prot.25126.", + "title": "Cover Image, Volume 85, Issue 5." + }, + { + "DOI": "10.1074/jbc.m117.777235", + "PMID": "28213515", + "authors": [ + { + "initials": "S", + "last": "Webb" + }, + { + "initials": "T", + "last": "Nagy" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "M", + "last": "Fried" + }, + { + "initials": "R", + "last": "Dutch" + } + ], + "pub_dict_key": "", + "reference_line": "Webb S, Nagy T, Moseley H, Fried M, Dutch R.\n \n Hendra virus fusion protein transmembrane domain contributes to pre-fusion protein stability.\n J Biol Chem.\n \n \n 2017 Apr 7;292(14):5685-5694. doi: 10.1074/jbc.M117.777235. Epub 2017 Feb 17. PubMed PMID:\n 28213515; PubMed Central PMCID:\n PMC5392564.", + "title": "Hendra virus fusion protein transmembrane domain contributes to pre-fusion protein stability." + }, + { + "DOI": "10.1186/s12859-017-1580-5", + "PMID": "28302053", + "authors": [ + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "M", + "last": "Astra" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Smelter A, Astra M, Moseley HN.\n \n A fast and efficient python library for interfacing with the Biological Magnetic Resonance Data Bank.\n BMC Bioinformatics.\n \n \n 2017 Mar 17;18(1):175. doi: 10.1186/s12859-017-1580-5. PubMed PMID:\n 28302053; PubMed Central PMCID:\n PMC5356280.", + "title": "A fast and efficient python library for interfacing with the Biological Magnetic Resonance Data Bank." + }, + { + "DOI": "10.1186/s12859-017-1580-5", + "PMID": "", + "authors": [ + { + "initials": "A", + "last": "Smelter" + }, + { + "initials": "M", + "last": "Astra" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Smelter A, Astra M, Moseley H.\n \n A fast and efficient python library for interfacing with the Biological Magnetic Resonance Data Bank.\n BMC Bioinformatics. 2017-3-; 18(1):-. doi: 10.1186/s12859-017-1580-5.", + "title": "A fast and efficient python library for interfacing with the Biological Magnetic Resonance Data Bank." + }, + { + "DOI": "10.1002/prot.25263", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "E", + "last": "Rouchka" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight R, Rouchka E, Moseley H.\n \n Perspectives and expectations in structural bioinformatics of metalloproteins.\n Proteins: Structure, Function, and Bioinformatics. 2017 March; 85(5):938-944. doi: 10.1002/prot.25263.", + "title": "Perspectives and expectations in structural bioinformatics of metalloproteins." + }, + { + "DOI": "10.1002/prot.25257", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "E", + "last": "Rouchka" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight R, Rouchka E, Moseley H.\n \n Aberrant coordination geometries discovered in the most abundant metalloproteins.\n Proteins: Structure, Function, and Bioinformatics. 2017 March; 85(5):885-907. doi: 10.1002/prot.25257.", + "title": "Aberrant coordination geometries discovered in the most abundant metalloproteins." + }, + { + "DOI": "10.1109/bibm.2017.8217835", + "PMID": "", + "authors": [ + { + "initials": "R", + "last": "Abeysinghe" + }, + { + "initials": "III", + "last": "Hinderer" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "L", + "last": "Cui" + } + ], + "pub_dict_key": "", + "reference_line": "Abeysinghe R, Hinderer III EW, Moseley HN, Cui L.\n \n Auditing Subtype Inconsistencies among Gene Ontology Concepts.\n The 2nd International Workshop on Semantics-Powered Data Analytics (SEPDA 2017) -- Bioinformatics and Biomedicine (BIBM), 2017 IEEE International Conference. 2017; :1242. doi: 10.1109/BIBM.2017.8217835.", + "title": "Auditing Subtype Inconsistencies among Gene Ontology Concepts." + }, + { + "DOI": "10.1007/s11306-017-1250-7", + "PMID": "", + "authors": [ + { + "initials": "D", + "last": "Verdegem" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "W", + "last": "Vemaelen" + }, + { + "initials": "AA", + "last": "Sanchez" + }, + { + "initials": "B", + "last": "Ghesqui\u00e8re" + } + ], + "pub_dict_key": "", + "reference_line": "Verdegem D, Moseley HN, Vemaelen W, Sanchez AA, Ghesqui\u00e8re B.\n \n MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites.\n Metabolomics. 2017; 13:123. doi: 10.1007/s11306-017-1250-7.", + "title": "MAIMS: A software tool for sensitive metabolic tracer analysis through the deconvolution of 13C mass isotopologue profiles of large composite metabolites." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN.\n MoseleyBioinformaticsLab GitHub Repositories. In: GitHub. GitHub: GitHub; 2016. Available from: https://github.com/MoseleyBioinformaticsLab.", + "title": "MoseleyBioinformaticsLab GitHub Repositories." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "E", + "last": "Rouchka" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight R, Rouchka E, Moseley H.\n \n A less biased analysis of metalloproteins' coordination geometries.\n Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics. BCB '15: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine; 09 09 2015 12 09 2015; Atlanta Georgia. New York, NY, USA: ACM; c2015.", + "title": "A less biased analysis of metalloproteins' coordination geometries." + }, + { + "DOI": "10.1371/journal.pone.0135410", + "PMID": "26305327", + "authors": [ + { + "initials": "N", + "last": "Nalabothula" + }, + { + "initials": "T", + "last": "Al-jumaily" + }, + { + "initials": "AM", + "last": "Eteleeb" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "S", + "last": "Xiaorong" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "EC", + "last": "Rouchka" + }, + { + "initials": "YN", + "last": "Fondufe-Mittendorf" + } + ], + "pub_dict_key": "", + "reference_line": "Nalabothula N, Al-jumaily T, Eteleeb AM, Flight RM, Xiaorong S, Moseley H, Rouchka EC, Fondufe-Mittendorf YN.\n \n Genome-Wide Profiling of PARP1 Reveals an Interplay with Gene Regulatory Regions and DNA Methylation.\n PLoS One.\n \n \n 2015;10(8):e0135410. doi: 10.1371/journal.pone.0135410. eCollection 2015. PubMed PMID:\n 26305327; PubMed Central PMCID:\n PMC4549251.", + "title": "Genome-Wide Profiling of PARP1 Reveals an Interplay with Gene Regulatory Regions and DNA Methylation." + }, + { + "DOI": "10.1371/journal.pone.0135410", + "PMID": "", + "authors": [ + { + "initials": "N", + "last": "Nalabothula" + }, + { + "initials": "T", + "last": "Al-jumaily" + }, + { + "initials": "A", + "last": "Eteleeb" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "S", + "last": "Xiaorong" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "E", + "last": "Rouchka" + }, + { + "initials": "Y", + "last": "Fondufe-Mittendorf" + } + ], + "pub_dict_key": "", + "reference_line": "Nalabothula N, Al-jumaily T, Eteleeb A, Flight R, Xiaorong S, Moseley H, Rouchka E, Fondufe-Mittendorf Y.\n \n Genome-Wide Profiling of PARP1 Reveals an Interplay with Gene Regulatory Regions and DNA Methylation.\n PLOS ONE. 2015-8-; 10(8):e0135410-. doi: 10.1371/journal.pone.0135410.", + "title": "Genome-Wide Profiling of PARP1 Reveals an Interplay with Gene Regulatory Regions and DNA Methylation." + }, + { + "DOI": "10.1002/prot.24834", + "PMID": "26009987", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "EC", + "last": "Rouchka" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight RM, Rouchka EC, Moseley HN.\n \n A less-biased analysis of metalloproteins reveals novel zinc coordination geometries.\n Proteins.\n \n \n 2015 Aug;83(8):1470-87. doi: 10.1002/prot.24834. Epub 2015 Jun 13. PubMed PMID:\n 26009987; PubMed Central PMCID:\n PMC4539273.", + "title": "A less-biased analysis of metalloproteins reveals novel zinc coordination geometries." + }, + { + "DOI": "10.1002/prot.24834", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "E", + "last": "Rouchka" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight R, Rouchka E, Moseley H.\n \n A less‐biased analysis of metalloproteins reveals novel zinc coordination geometries.\n Proteins: Structure, Function, and Bioinformatics. 2015 June; 83(8):1470-1487. doi: 10.1002/prot.24834.", + "title": "A less‐biased analysis of metalloproteins reveals novel zinc coordination geometries." + }, + { + "DOI": "10.1002/mrc.4199", + "PMID": "25616249", + "authors": [ + { + "initials": "AN", + "last": "Lane" + }, + { + "initials": "S", + "last": "Arumugam" + }, + { + "initials": "PK", + "last": "Lorkiewicz" + }, + { + "initials": "RM", + "last": "Higashi" + }, + { + "initials": "S", + "last": "Laulh\u00e9" + }, + { + "initials": "MH", + "last": "Nantz" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "TW", + "last": "Fan" + } + ], + "pub_dict_key": "", + "reference_line": "Lane AN, Arumugam S, Lorkiewicz PK, Higashi RM, Laulh\u00e9 S, Nantz MH, Moseley HN, Fan TW.\n \n Chemoselective detection and discrimination of carbonyl-containing compounds in metabolite mixtures by 1H-detected 15N nuclear magnetic resonance.\n Magn Reson Chem.\n \n \n 2015 May;53(5):337-43. doi: 10.1002/mrc.4199. Epub 2015 Jan 23. PubMed PMID:\n 25616249; PubMed Central PMCID:\n PMC4409496.", + "title": "Chemoselective detection and discrimination of carbonyl-containing compounds in metabolite mixtures by 1H-detected 15N nuclear magnetic resonance." + }, + { + "DOI": "10.1002/mrc.4199", + "PMID": "", + "authors": [ + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "S", + "last": "Arumugam" + }, + { + "initials": "P", + "last": "Lorkiewicz" + }, + { + "initials": "R", + "last": "Higashi" + }, + { + "initials": "S", + "last": "Laulh\u00e9" + }, + { + "initials": "M", + "last": "Nantz" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "T", + "last": "Fan" + } + ], + "pub_dict_key": "", + "reference_line": "Lane A, Arumugam S, Lorkiewicz P, Higashi R, Laulh\u00e9 S, Nantz M, Moseley H, Fan T.\n \n Chemoselective detection and discrimination of carbonyl-containing compounds in metabolite mixtures by 1 H-detected 15 N nuclear magnetic resonance.\n Magnetic Resonance in Chemistry. 2015 May; 53(5):337-343. doi: 10.1002/mrc.4199.", + "title": "Chemoselective detection and discrimination of carbonyl-containing compounds in metabolite mixtures by 1 H-detected 15 N nuclear magnetic resonance." + }, + { + "DOI": "10.1145/2808719.2811424", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "EC", + "last": "Rouchka" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight RM, Rouchka EC, Moseley HN.\n \n A less biased analysis of metalloproteins reveals novel zinc coordination geometries.\n BCB '15 Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics. 2015; :493. doi: 10.1145/2808719.2811424.", + "title": "A less biased analysis of metalloproteins reveals novel zinc coordination geometries." + }, + { + "DOI": "10.1186/1471-2105-15-s10-p31", + "PMID": "", + "authors": [ + { + "initials": "S", + "last": "Yao" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Yao S, Flight R, Moseley H.\n \n Coordination characterization of zinc metalloproteins.\n BMC Bioinformatics. 2014 September; 15(S10):-. doi: 10.1186/1471-2105-15-S10-P31.", + "title": "Coordination characterization of zinc metalloproteins." + }, + { + "DOI": "10.1186/1471-2105-15-s10-p36", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "T", + "last": "Fan" + }, + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Fan T, Lane A, Moseley H.\n \n Development of large-scale metabolite identification methods for metabolomics.\n BMC Bioinformatics. 2014 September; 15(S10):-. doi: 10.1186/1471-2105-15-S10-P36.", + "title": "Development of large-scale metabolite identification methods for metabolomics." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "A", + "last": "Eteleeb" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "E", + "last": "Rouchka" + } + ], + "pub_dict_key": "", + "reference_line": "Eteleeb A, Moseley H, Rouchka E.\n \n A comparison of combined p-value methods for gene differential expression using RNA-seq data.\n Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. BCB '14: ACM-BCB '14; 20 09 2014 23 09 2014; Newport Beach California. New York, NY, USA: ACM; c2014.", + "title": "A comparison of combined p-value methods for gene differential expression using RNA-seq data." + }, + { + "DOI": "10.3389/fgene.2014.00237", + "PMID": "25120557", + "authors": [ + { + "initials": "JM", + "last": "Mitchell" + }, + { + "initials": "TW", + "last": "Fan" + }, + { + "initials": "AN", + "last": "Lane" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell JM, Fan TW, Lane AN, Moseley HN.\n \n Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics.\n Front Genet.\n \n \n 2014;5:237. doi: 10.3389/fgene.2014.00237. eCollection 2014. PubMed PMID:\n 25120557; PubMed Central PMCID:\n PMC4112935.", + "title": "Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics." + }, + { + "DOI": "10.3389/fgene.2014.00237", + "PMID": "", + "authors": [ + { + "initials": "J", + "last": "Mitchell" + }, + { + "initials": "T", + "last": "Fan" + }, + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Mitchell J, Fan T, Lane A, Moseley H.\n \n Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics.\n Frontiers in Genetics. 2014 July; 5:-. doi: 10.3389/fgene.2014.00237.", + "title": "Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics." + }, + { + "DOI": "10.1007/978-1-4939-1258-2_11", + "PMID": "25270929", + "authors": [ + { + "initials": "RM", + "last": "Higashi" + }, + { + "initials": "TW", + "last": "Fan" + }, + { + "initials": "PK", + "last": "Lorkiewicz" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "AN", + "last": "Lane" + } + ], + "pub_dict_key": "", + "reference_line": "Higashi RM, Fan TW, Lorkiewicz PK, Moseley HN, Lane AN.\n \n Stable isotope-labeled tracers for metabolic pathway elucidation by GC-MS and FT-MS.\n Methods Mol Biol.\n \n \n 2014;1198:147-67. doi: 10.1007/978-1-4939-1258-2_11. PubMed PMID:\n 25270929; PubMed Central PMCID:\n PMC4337027.", + "title": "Stable isotope-labeled tracers for metabolic pathway elucidation by GC-MS and FT-MS." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "R", + "last": "Higashi" + }, + { + "initials": "T", + "last": "Fan" + }, + { + "initials": "P", + "last": "Lorkiewicz" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "A", + "last": "Lane" + } + ], + "pub_dict_key": "", + "reference_line": "Higashi R, Fan T, Lorkiewicz P, Moseley H, Lane A.\n \n Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS.\n \n In:\n \n \n Methods in Molecular Biology\n \n [Internet]\n \n New York, NY: Springer New York; 2014. Chapter Chapter 11; 147-167p.\n \n \n Available from: http://link.springer.com/10.1007/978-1-4939-1258-2_11.", + "title": "Stable Isotope-Labeled Tracers for Metabolic Pathway Elucidation by GC-MS and FT-MS." + }, + { + "DOI": "10.3390/metabo3040853", + "PMID": "24404440", + "authors": [ + { + "initials": "WJ", + "last": "Carreer" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Carreer WJ, Flight RM, Moseley HN.\n \n A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets.\n Metabolites.\n \n \n 2013 Sep 25;3(4). doi: 10.3390/metabo3040853. PubMed PMID:\n 24404440; PubMed Central PMCID:\n PMC3882318.", + "title": "A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets." + }, + { + "DOI": "10.5936/csbj.201301006", + "PMID": "23667718", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN.\n \n Error Analysis and Propagation in Metabolomics Data Analysis.\n Comput Struct Biotechnol J.\n \n \n 2013 Jan 1;4(5). doi: 10.5936/csbj.201301006. PubMed PMID:\n 23667718; PubMed Central PMCID:\n PMC3647477.", + "title": "Error Analysis and Propagation in Metabolomics Data Analysis." + }, + { + "DOI": "10.5936/csbj.201301006", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H.\n \n ERROR ANALYSIS AND PROPAGATION IN METABOLOMICS DATA ANALYSIS.\n Computational and Structural Biotechnology Journal. 2013 January; 4(5):e201301006-. doi: 10.5936/csbj.201301006.", + "title": "ERROR ANALYSIS AND PROPAGATION IN METABOLOMICS DATA ANALYSIS." + }, + { + "DOI": "10.1186/1741-7007-10-74", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "A", + "last": "Belshoff" + }, + { + "initials": "R", + "last": "Higashi" + }, + { + "initials": "T", + "last": "Fan" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T.\n \n Erratum to: A novel deconvolution method for modeling UDP-N-acetyl-D-glucosaminebiosynthetic pathways based on 13C mass isotopologue profiles undernon-steady-state conditions.\n BMC Biology. 2012 August; 10(1):-. doi: 10.1186/1741-7007-10-74.", + "title": "Erratum to: A novel deconvolution method for modeling UDP-N-acetyl-D-glucosaminebiosynthetic pathways based on 13C mass isotopologue profiles undernon-steady-state conditions." + }, + { + "DOI": "10.1186/1471-2105-13-s12-a1", + "PMID": "", + "authors": [ + { + "initials": "E", + "last": "Rouchka" + }, + { + "initials": "R", + "last": "Flight" + }, + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Rouchka E, Flight R, Moseley H.\n \n Proceedings of the Eleventh Annual UT-ORNL-KBRIN Bioinformatics Summit 2012.\n BMC Bioinformatics. 2012-7-; 13(S12):-. doi: 10.1186/1471-2105-13-S12-A1.", + "title": "Proceedings of the Eleventh Annual UT-ORNL-KBRIN Bioinformatics Summit 2012." + }, + { + "DOI": "10.1016/j.pharmthera.2011.12.007", + "PMID": "22212615", + "authors": [ + { + "initials": "TW", + "last": "Fan" + }, + { + "initials": "PK", + "last": "Lorkiewicz" + }, + { + "initials": "K", + "last": "Sellers" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "RM", + "last": "Higashi" + }, + { + "initials": "AN", + "last": "Lane" + } + ], + "pub_dict_key": "", + "reference_line": "Fan TW, Lorkiewicz PK, Sellers K, Moseley HN, Higashi RM, Lane AN.\n \n Stable isotope-resolved metabolomics and applications for drug development.\n Pharmacol Ther.\n \n \n 2012 Mar;133(3):366-91. doi: 10.1016/j.pharmthera.2011.12.007. Epub 2011 Dec 23. Review. PubMed PMID:\n 22212615; PubMed Central PMCID:\n PMC3471671.", + "title": "Stable isotope-resolved metabolomics and applications for drug development." + }, + { + "DOI": "10.1016/j.pharmthera.2011.12.007", + "PMID": "", + "authors": [ + { + "initials": "T", + "last": "Fan" + }, + { + "initials": "P", + "last": "Lorkiewicz" + }, + { + "initials": "K", + "last": "Sellers" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "R", + "last": "Higashi" + }, + { + "initials": "A", + "last": "Lane" + } + ], + "pub_dict_key": "", + "reference_line": "Fan T, Lorkiewicz P, Sellers K, Moseley H, Higashi R, Lane A.\n \n Stable isotope-resolved metabolomics and applications for drug development.\n Pharmacology & Therapeutics. 2012 March; 133(3):366-391. doi: 10.1016/j.pharmthera.2011.12.007.", + "title": "Stable isotope-resolved metabolomics and applications for drug development." + }, + { + "DOI": "10.1186/1471-2105-13-s12-a1", + "PMID": "", + "authors": [ + { + "initials": "EC", + "last": "Rouchka" + }, + { + "initials": "RM", + "last": "Flight" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Rouchka EC, Flight RM, Moseley HN.\n \n Proceedings of the Eleventh Annual UT-ORNL-KBRIN Bioinformatics Summit 2012.\n BMC Bioinformatics. 2012; 13:A1. doi: doi:10.1186/1471-2105-13-S12-A1.", + "title": "Proceedings of the Eleventh Annual UT-ORNL-KBRIN Bioinformatics Summit 2012." + }, + { + "DOI": "10.1186/1741-7007-9-37", + "PMID": "21627825", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "AN", + "last": "Lane" + }, + { + "initials": "AC", + "last": "Belshoff" + }, + { + "initials": "RM", + "last": "Higashi" + }, + { + "initials": "TW", + "last": "Fan" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN, Lane AN, Belshoff AC, Higashi RM, Fan TW.\n \n A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions.\n BMC Biol.\n \n \n 2011 May 31;9:37. doi: 10.1186/1741-7007-9-37. PubMed PMID:\n 21627825; PubMed Central PMCID:\n PMC3126751.", + "title": "A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions." + }, + { + "DOI": "10.1186/1741-7007-9-37", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "A", + "last": "Belshoff" + }, + { + "initials": "R", + "last": "Higashi" + }, + { + "initials": "T", + "last": "Fan" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Lane A, Belshoff A, Higashi R, Fan T.\n \n A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions.\n BMC Biology. 2011 May; 9(1):-. doi: 10.1186/1741-7007-9-37.", + "title": "A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "RM", + "last": "Higashi" + }, + { + "initials": "TW", + "last": "Fan" + }, + { + "initials": "AN", + "last": "Lane" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN, Higashi RM, Fan TW, Lane AN.\n \n Metabolic Modeling of Converging Metabolic Pathways: Analysis of Non-Steady State Stable Isotope-Resolve Metabolism of UDP-GlcNAc and UDP-GalNAc.\n \n In:\n \n \n Pellegrini M, Fred A, Filipe J, Gamboa H, editors.\n \n BIOINFORMATICS 2011\n \n Portugal: SciTePress; 2011. p.108-115.", + "title": "Metabolic Modeling of Converging Metabolic Pathways: Analysis of Non-Steady State Stable Isotope-Resolve Metabolism of UDP-GlcNAc and UDP-GalNAc." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "H.N.B.", + "last": "Moseley" + }, + { + "initials": "R.M.", + "last": "Higashi" + }, + { + "initials": "T.W.-M.", + "last": "Fan" + }, + { + "initials": "A.N.", + "last": "Lane" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley, H.N.B., Higashi, R.M., Fan, T.W.-M., Lane, A.N..\n \n Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc.\n BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. 2011; :108-115.", + "title": "Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "H.N.B.", + "last": "Moseley" + }, + { + "initials": "R.M.", + "last": "Higashi" + }, + { + "initials": "T.W.-M.", + "last": "Fan" + }, + { + "initials": "A.N.", + "last": "Lane" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley, H.N.B., Higashi, R.M., Fan, T.W.-M., Lane, A.N..\n \n Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc.\n BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms; 2011; c2011.", + "title": "Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc." + }, + { + "DOI": "10.1007/s10858-010-9448-2", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "L", + "last": "Sperling" + }, + { + "initials": "C", + "last": "Rienstra" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Sperling L, Rienstra C.\n \n Automated protein resonance assignments of magic angle spinning solid-state NMR spectra of β1 immunoglobulin binding domain of protein G (GB1).\n Journal of Biomolecular NMR. 2010 October; 48(3):123-128. doi: 10.1007/s10858-010-9448-2.", + "title": "Automated protein resonance assignments of magic angle spinning solid-state NMR spectra of β1 immunoglobulin binding domain of protein G (GB1)." + }, + { + "DOI": "10.1186/1471-2105-11-139", + "PMID": "20236542", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN.\n \n Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry.\n BMC Bioinformatics.\n \n \n 2010 Mar 17;11:139. doi: 10.1186/1471-2105-11-139. PubMed PMID:\n 20236542; PubMed Central PMCID:\n PMC2848236.", + "title": "Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry." + }, + { + "DOI": "10.1186/1471-2105-11-139", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H.\n \n Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry.\n BMC Bioinformatics. 2010-3-; 11(1):-. doi: 10.1186/1471-2105-11-139.", + "title": "Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry." + }, + { + "DOI": "10.1016/j.aca.2009.08.032", + "PMID": "", + "authors": [ + { + "initials": "A", + "last": "Lane" + }, + { + "initials": "T", + "last": "Fan" + }, + { + "initials": "Z", + "last": "Xie" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "R", + "last": "Higashi" + } + ], + "pub_dict_key": "", + "reference_line": "Lane A, Fan T, Xie Z, Moseley H, Higashi R.\n \n Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR.\n Analytica Chimica Acta. 2009 October; 651(2):201-208. doi: 10.1016/j.aca.2009.08.032.", + "title": "Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR." + }, + { + "DOI": "10.1007/s10858-006-0027-5", + "PMID": "16645816", + "authors": [ + { + "initials": "GJ", + "last": "Kornhaber" + }, + { + "initials": "D", + "last": "Snyder" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Kornhaber GJ, Snyder D, Moseley HN, Montelione GT.\n \n Identification of zinc-ligated cysteine residues based on 13Calpha and 13Cbeta chemical shift data.\n J Biomol NMR.\n \n \n 2006 Apr;34(4):259-69. doi: 10.1007/s10858-006-0027-5. PubMed PMID:\n 16645816.", + "title": "Identification of zinc-ligated cysteine residues based on 13Calpha and 13Cbeta chemical shift data." + }, + { + "DOI": "10.1007/s10858-006-0027-5", + "PMID": "", + "authors": [ + { + "initials": "G", + "last": "Kornhaber" + }, + { + "initials": "D", + "last": "Snyder" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Kornhaber G, Snyder D, Moseley H, Montelione G.\n \n Identification of Zinc-ligated Cysteine Residues Based on 13Cα and 13Cβ Chemical Shift Data.\n Journal of Biomolecular NMR. 2006 April; 34(4):259-269. doi: 10.1007/s10858-006-0027-5.", + "title": "Identification of Zinc-ligated Cysteine Residues Based on 13Cα and 13Cβ Chemical Shift Data." + }, + { + "DOI": "10.1002/prot.20840", + "PMID": "16395675", + "authors": [ + { + "initials": "MC", + "last": "Baran" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "JM", + "last": "Aramini" + }, + { + "initials": "MJ", + "last": "Bayro" + }, + { + "initials": "D", + "last": "Monleon" + }, + { + "initials": "JY", + "last": "Locke" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Baran MC, Moseley HN, Aramini JM, Bayro MJ, Monleon D, Locke JY, Montelione GT.\n \n SPINS: a laboratory information management system for organizing and archiving intermediate and final results from NMR protein structure determinations.\n Proteins.\n \n \n 2006 Mar 1;62(4):843-51. doi: 10.1002/prot.20840. PubMed PMID:\n 16395675.", + "title": "SPINS: a laboratory information management system for organizing and archiving intermediate and final results from NMR protein structure determinations." + }, + { + "DOI": "10.1002/prot.20840", + "PMID": "", + "authors": [ + { + "initials": "M", + "last": "Baran" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "J", + "last": "Aramini" + }, + { + "initials": "M", + "last": "Bayro" + }, + { + "initials": "D", + "last": "Monleon" + }, + { + "initials": "J", + "last": "Locke" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Baran M, Moseley H, Aramini J, Bayro M, Monleon D, Locke J, Montelione G.\n \n SPINS: A laboratory information management system for organizing and archiving intermediate and final results from NMR protein structure determinations.\n Proteins: Structure, Function, and Bioinformatics. 2006 January; 62(4):843-851. doi: 10.1002/prot.20840.", + "title": "SPINS: A laboratory information management system for organizing and archiving intermediate and final results from NMR protein structure determinations." + }, + { + "DOI": "10.1016/s0076-6879(05)94005-6", + "PMID": "15808219", + "authors": [ + { + "initials": "YJ", + "last": "Huang" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "MC", + "last": "Baran" + }, + { + "initials": "C", + "last": "Arrowsmith" + }, + { + "initials": "R", + "last": "Powers" + }, + { + "initials": "R", + "last": "Tejero" + }, + { + "initials": "T", + "last": "Szyperski" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "", + "title": "An integrated platform for automated analysis of protein NMR structures." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "Y", + "last": "Huang" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "M", + "last": "Baran" + }, + { + "initials": "C", + "last": "Arrowsmith" + }, + { + "initials": "R", + "last": "Powers" + }, + { + "initials": "R", + "last": "Tejero" + }, + { + "initials": "T", + "last": "Szyperski" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Huang Y, Moseley H, Baran M, Arrowsmith C, Powers R, Tejero R, Szyperski T, Montelione G.\n \n An Integrated Platform for Automated Analysis of Protein NMR Structures.\n \n In:\n \n \n Methods in Enzymology\n \n [Internet]\n \n Elsevier; 2005. 111-141p.\n \n \n Available from: https://linkinghub.elsevier.com/retrieve/pii/S0076687905940056.", + "title": "An Integrated Platform for Automated Analysis of Protein NMR Structures." + }, + { + "DOI": "10.1002/chin.200445293", + "PMID": "", + "authors": [ + { + "initials": "M", + "last": "Baran" + }, + { + "initials": "Y", + "last": "Huang" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Baran M, Huang Y, Moseley H, Montelione G.\n \n Automated Analysis of Protein NMR Assignments and Structures.\n ChemInform. 2004 November; 35(45):-. doi: 10.1002/chin.200445293.", + "title": "Automated Analysis of Protein NMR Assignments and Structures." + }, + { + "DOI": "10.1016/j.jmr.2004.06.015", + "PMID": "15388090", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "N", + "last": "Riaz" + }, + { + "initials": "JM", + "last": "Aramini" + }, + { + "initials": "T", + "last": "Szyperski" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN, Riaz N, Aramini JM, Szyperski T, Montelione GT.\n \n A generalized approach to automated NMR peak list editing: application to reduced dimensionality triple resonance spectra.\n J Magn Reson.\n \n \n 2004 Oct;170(2):263-77. doi: 10.1016/j.jmr.2004.06.015. PubMed PMID:\n 15388090.", + "title": "A generalized approach to automated NMR peak list editing: application to reduced dimensionality triple resonance spectra." + }, + { + "DOI": "10.1016/j.jmr.2004.06.015", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "N", + "last": "Riaz" + }, + { + "initials": "J", + "last": "Aramini" + }, + { + "initials": "T", + "last": "Szyperski" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Riaz N, Aramini J, Szyperski T, Montelione G.\n \n A generalized approach to automated NMR peak list editing: application to reduced dimensionality triple resonance spectra.\n Journal of Magnetic Resonance. 2004 October; 170(2):263-277. doi: 10.1016/j.jmr.2004.06.015.", + "title": "A generalized approach to automated NMR peak list editing: application to reduced dimensionality triple resonance spectra." + }, + { + "DOI": "10.1021/cr030408p", + "PMID": "", + "authors": [ + { + "initials": "M", + "last": "Baran" + }, + { + "initials": "Y", + "last": "Huang" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Baran M, Huang Y, Moseley H, Montelione G.\n \n Automated Analysis of Protein NMR Assignments and Structures.\n Chemical Reviews. 2004 July; 104(8):3541-3556. doi: 10.1021/cr030408p.", + "title": "Automated Analysis of Protein NMR Assignments and Structures." + }, + { + "DOI": "10.1023/b:jnmr.0000015420.44364.06", + "PMID": "14872126", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "G", + "last": "Sahota" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN, Sahota G, Montelione GT.\n \n Assignment validation software suite for the evaluation and presentation of protein resonance assignment data.\n J Biomol NMR.\n \n \n 2004 Apr;28(4):341-55. doi: 10.1023/B:JNMR.0000015420.44364.06. PubMed PMID:\n 14872126.", + "title": "Assignment validation software suite for the evaluation and presentation of protein resonance assignment data." + }, + { + "DOI": "10.1023/b:jnmr.0000015420.44364.06", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "G", + "last": "Sahota" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Sahota G, Montelione G.\n \n Assignment validation software suite for the evaluation and presentation of protein resonance assignment data.\n Journal of Biomolecular NMR. 2004 April; 28(4):341-355. doi: 10.1023/B:JNMR.0000015420.44364.06.", + "title": "Assignment validation software suite for the evaluation and presentation of protein resonance assignment data." + }, + { + "DOI": "10.1110/ps.0300203", + "PMID": "12761394", + "authors": [ + { + "initials": "D", + "last": "Zheng" + }, + { + "initials": "YJ", + "last": "Huang" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "R", + "last": "Xiao" + }, + { + "initials": "J", + "last": "Aramini" + }, + { + "initials": "GV", + "last": "Swapna" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Zheng D, Huang YJ, Moseley HN, Xiao R, Aramini J, Swapna GV, Montelione GT.\n \n Automated protein fold determination using a minimal NMR constraint strategy.\n Protein Sci.\n \n \n 2003 Jun;12(6):1232-46. doi: 10.1110/ps.0300203. PubMed PMID:\n 12761394; PubMed Central PMCID:\n PMC2323888.", + "title": "Automated protein fold determination using a minimal NMR constraint strategy." + }, + { + "DOI": "10.1110/ps.0300203", + "PMID": "", + "authors": [ + { + "initials": "D", + "last": "Zheng" + }, + { + "initials": "Y", + "last": "Huang" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "R", + "last": "Xiao" + }, + { + "initials": "J", + "last": "Aramini" + }, + { + "initials": "G", + "last": "Swapna" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Zheng D, Huang Y, Moseley H, Xiao R, Aramini J, Swapna G, Montelione G.\n \n Automated protein fold determination using a minimal NMR constraint strategy.\n Protein Science. 2003 June; 12(6):1232-1246. doi: 10.1110/ps.0300203.", + "title": "Automated protein fold determination using a minimal NMR constraint strategy." + }, + { + "DOI": "10.1073/pnas.122224599", + "PMID": "12060747", + "authors": [ + { + "initials": "T", + "last": "Szyperski" + }, + { + "initials": "DC", + "last": "Yeh" + }, + { + "initials": "DK", + "last": "Sukumaran" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Szyperski T, Yeh DC, Sukumaran DK, Moseley HN, Montelione GT.\n \n Reduced-dimensionality NMR spectroscopy for high-throughput protein resonance assignment.\n Proc Natl Acad Sci U S A.\n \n \n 2002 Jun 11;99(12):8009-14. doi: 10.1073/pnas.122224599. PubMed PMID:\n 12060747; PubMed Central PMCID:\n PMC123011.", + "title": "Reduced-dimensionality NMR spectroscopy for high-throughput protein resonance assignment." + }, + { + "DOI": "10.1073/pnas.122224599", + "PMID": "", + "authors": [ + { + "initials": "T", + "last": "Szyperski" + }, + { + "initials": "D", + "last": "Yeh" + }, + { + "initials": "D", + "last": "Sukumaran" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Szyperski T, Yeh D, Sukumaran D, Moseley H, Montelione G.\n \n Reduced-dimensionality NMR spectroscopy for high-throughput protein resonance assignment.\n Proceedings of the National Academy of Sciences. 2002 June; 99(12):8009-8014. doi: 10.1073/pnas.122224599.", + "title": "Reduced-dimensionality NMR spectroscopy for high-throughput protein resonance assignment." + }, + { + "DOI": "10.1023/a:1020499629298", + "PMID": "12836666", + "authors": [ + { + "initials": "D", + "last": "Monle\u00f3n" + }, + { + "initials": "K", + "last": "Colson" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "C", + "last": "Anklin" + }, + { + "initials": "R", + "last": "Oswald" + }, + { + "initials": "T", + "last": "Szyperski" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Monle\u00f3n D, Colson K, Moseley HN, Anklin C, Oswald R, Szyperski T, Montelione GT.\n \n Rapid analysis of protein backbone resonance assignments using cryogenic probes, a distributed Linux-based computing architecture, and an integrated set of spectral analysis tools.\n J Struct Funct Genomics.\n \n \n 2002;2(2):93-101. doi: 10.1023/a:1020499629298. PubMed PMID:\n 12836666.", + "title": "Rapid analysis of protein backbone resonance assignments using cryogenic probes, a distributed Linux-based computing architecture, and an integrated set of spectral analysis tools." + }, + { + "DOI": "10.1023/a:1020499629298", + "PMID": "", + "authors": [ + { + "initials": "D", + "last": "Monle\u00f3n" + }, + { + "initials": "K", + "last": "Colson" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "C", + "last": "Anklin" + }, + { + "initials": "R", + "last": "Oswald" + }, + { + "initials": "T", + "last": "Szyperski" + }, + { + "initials": "T.", + "last": "Gaetano" + } + ], + "pub_dict_key": "", + "reference_line": "Monle\u00f3n D, Colson K, Moseley H, Anklin C, Oswald R, Szyperski T, Gaetano T. Montelione.\n Journal of Structural and Functional Genomics. 2002; 2(2):93-101. doi: 10.1023/A:1020499629298.", + "title": "" + }, + { + "DOI": "10.1023/a:1020940806745", + "PMID": "", + "authors": [ + { + "initials": "M", + "last": "Baran" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "G", + "last": "Sahota" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Baran M, Moseley H, Sahota G, Montelione G.\n Journal of Biomolecular NMR. 2002; 24(2):113-121. doi: 10.1023/A:1020940806745.", + "title": "" + }, + { + "DOI": "10.1100/tsw.2002.16", + "PMID": "", + "authors": [ + { + "initials": "G", + "last": "Montelione" + }, + { + "initials": "S", + "last": "Anderson" + }, + { + "initials": "T", + "last": "Acton" + }, + { + "initials": "B", + "last": "Dixon" + }, + { + "initials": "Y", + "last": "Huang" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "D", + "last": "Monleon" + }, + { + "initials": "K", + "last": "Shukla" + }, + { + "initials": "G", + "last": "Swapna" + }, + { + "initials": "R", + "last": "Tejero" + } + ], + "pub_dict_key": "", + "reference_line": "Montelione G, Anderson S, Acton T, Dixon B, Huang Y, Moseley H, Monleon D, Shukla K, Swapna G, Tejero R.\n \n Structural Proteomics of Eukaryotic Gene Families.\n The Scientific World JOURNAL. 2002; 2:32-32. doi: 10.1100/tsw.2002.16.", + "title": "Structural Proteomics of Eukaryotic Gene Families." + }, + { + "DOI": "10.1016/s0076-6879(01)39311-4", + "PMID": "11462827", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "D", + "last": "Monleon" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN, Monleon D, Montelione GT.\n \n Automatic determination of protein backbone resonance assignments from triple resonance nuclear magnetic resonance data.\n Methods Enzymol.\n \n \n 2001;339:91-108. doi: 10.1016/s0076-6879(01)39311-4. PubMed PMID:\n 11462827.", + "title": "Automatic determination of protein backbone resonance assignments from triple resonance nuclear magnetic resonance data." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "D", + "last": "Monleon" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Monleon D, Montelione G.\n \n Automatic Determination of Protein Backbone Resonance Assignments from Triple Resonance Nuclear Magnetic Resonance Data.\n \n In:\n \n \n Methods in Enzymology\n \n [Internet]\n \n Elsevier; 2001. 91-108p.\n \n \n Available from: https://linkinghub.elsevier.com/retrieve/pii/S0076687901393114.", + "title": "Automatic Determination of Protein Backbone Resonance Assignments from Triple Resonance Nuclear Magnetic Resonance Data." + }, + { + "DOI": "10.1016/s0959-440x(99)00019-6", + "PMID": "10508776", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "GT", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN, Montelione GT.\n \n Automated analysis of NMR assignments and structures for proteins.\n Curr Opin Struct Biol.\n \n \n 1999 Oct;9(5):635-42. doi: 10.1016/s0959-440x(99)00019-6. Review. PubMed PMID:\n 10508776.", + "title": "Automated analysis of NMR assignments and structures for proteins." + }, + { + "DOI": "10.1016/s0959-440x(99)00019-6", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "G", + "last": "Montelione" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Montelione G.\n \n Automated analysis of NMR assignments and structures for proteins.\n Current Opinion in Structural Biology. 1999 October; 9(5):635-642. doi: 10.1016/S0959-440X(99)00019-6.", + "title": "Automated analysis of NMR assignments and structures for proteins." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "NR", + "last": "Krishna" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Krishna NR, Moseley HN.\n \n Complete Relaxation and Conformational Exchange Matrix Analysis of NOESY Spectra of Reversibly Forming Ligand Receptor Complexes: Application to Transferred NOESY.\n \n In:\n \n \n Krishna NR, Berliner LJ, editors.\n \n Biological Magnetic Resonance\n \n Vol 17 ed. New York: Plenum Press; 1999.", + "title": "Complete Relaxation and Conformational Exchange Matrix Analysis of NOESY Spectra of Reversibly Forming Ligand Receptor Complexes: Application to Transferred NOESY." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN.\n Implementation and Application of Complete Relaxation and Conformational Exchange Matrix Analysis of NOESY Spectra. 1998.", + "title": "Implementation and Application of Complete Relaxation and Conformational Exchange Matrix Analysis of NOESY Spectra." + }, + { + "DOI": "10.1021/bi970242k", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "W", + "last": "Lee" + }, + { + "initials": "C", + "last": "Arrowsmith" + }, + { + "initials": "N", + "last": "Krishna" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Lee W, Arrowsmith C, Krishna N.\n \n Quantitative Determination of Conformational, Dynamic, and Kinetic Parameters of a Ligand-Protein/DNA Complex from a Complete Relaxation and Conformational Exchange Matrix Analysis of Intermolecular Transferred NOESY.\n Biochemistry. 1997 May; 36(18):5293-5299. doi: 10.1021/bi970242k.", + "title": "Quantitative Determination of Conformational, Dynamic, and Kinetic Parameters of a Ligand-Protein/DNA Complex from a Complete Relaxation and Conformational Exchange Matrix Analysis of Intermolecular Transferred NOESY." + }, + { + "DOI": "10.1007/bf00124470", + "PMID": "8951648", + "authors": [ + { + "initials": "EV", + "last": "Curto" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "NR", + "last": "Krishna" + } + ], + "pub_dict_key": "", + "reference_line": "Curto EV, Moseley HN, Krishna NR.\n \n CORCEMA evaluation of the potential role of intermolecular transferred NOESY in the characterization of ligand-receptor complexes.\n J Comput Aided Mol Des.\n \n \n 1996 Oct;10(5):361-71. doi: 10.1007/BF00124470. PubMed PMID:\n 8951648.", + "title": "CORCEMA evaluation of the potential role of intermolecular transferred NOESY in the characterization of ligand-receptor complexes." + }, + { + "DOI": "10.1006/jmrb.1995.1129", + "PMID": "7670757", + "authors": [ + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "EV", + "last": "Curto" + }, + { + "initials": "NR", + "last": "Krishna" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley HN, Curto EV, Krishna NR.\n \n Complete relaxation and conformational exchange matrix (CORCEMA) analysis of NOESY spectra of interacting systems; two-dimensional transferred NOESY.\n J Magn Reson B.\n \n \n 1995 Sep;108(3):243-61. doi: 10.1006/jmrb.1995.1129. PubMed PMID:\n 7670757.", + "title": "Complete relaxation and conformational exchange matrix (CORCEMA) analysis of NOESY spectra of interacting systems; two-dimensional transferred NOESY." + }, + { + "DOI": "10.1006/jmrb.1995.1129", + "PMID": "", + "authors": [ + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "E", + "last": "Curto" + }, + { + "initials": "N", + "last": "Krishna" + } + ], + "pub_dict_key": "", + "reference_line": "Moseley H, Curto E, Krishna N.\n \n Complete Relaxation and Conformational Exchange Matrix (CORCEMA) Analysis of NOESY Spectra of Interacting Systems; Two-Dimensional Transferred NOESY.\n Journal of Magnetic Resonance, Series B. 1995 September; 108(3):243-261. doi: 10.1006/jmrb.1995.1129.", + "title": "Complete Relaxation and Conformational Exchange Matrix (CORCEMA) Analysis of NOESY Spectra of Interacting Systems; Two-Dimensional Transferred NOESY." + }, + { + "DOI": "10.1006/jmrb.1995.1092", + "PMID": "7788101", + "authors": [ + { + "initials": "PL", + "last": "Jackson" + }, + { + "initials": "HN", + "last": "Moseley" + }, + { + "initials": "NR", + "last": "Krishna" + } + ], + "pub_dict_key": "", + "reference_line": "Jackson PL, Moseley HN, Krishna NR.\n \n Relative effects of protein-mediated and ligand-mediated spin-diffusion pathways on transferred NOESY, and implications on the accuracy of the bound ligand conformation.\n J Magn Reson B.\n \n \n 1995 Jun;107(3):289-92. doi: 10.1006/jmrb.1995.1092. PubMed PMID:\n 7788101.", + "title": "Relative effects of protein-mediated and ligand-mediated spin-diffusion pathways on transferred NOESY, and implications on the accuracy of the bound ligand conformation." + }, + { + "DOI": "10.1006/jmrb.1995.1092", + "PMID": "", + "authors": [ + { + "initials": "P", + "last": "Jackson" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "N", + "last": "Krishna" + } + ], + "pub_dict_key": "", + "reference_line": "Jackson P, Moseley H, Krishna N.\n \n Relative Effects of Protein-Mediated and Ligand-Mediated Spin-Diffusion Pathways on Transferred NOESY, and Implications on the Accuracy of the Bound Ligand Conformation.\n Journal of Magnetic Resonance, Series B. 1995 June; 107(3):289-292. doi: 10.1006/jmrb.1995.1092.", + "title": "Relative Effects of Protein-Mediated and Ligand-Mediated Spin-Diffusion Pathways on Transferred NOESY, and Implications on the Accuracy of the Bound Ligand Conformation." + }, + { + "DOI": "", + "PMID": "", + "authors": [], + "pub_dict_key": "", + "reference_line": "The UAB Research Foundation, assignee. \n Method for analyzing 2D transferred noesy spectra of molecules undergoing multistate conformational exchange.\n USA US5668734 A. 1995.", + "title": "Method for analyzing 2D transferred noesy spectra of molecules undergoing multistate conformational exchange." + }, + { + "DOI": "10.1006/immu.1994.1044", + "PMID": "", + "authors": [ + { + "initials": "C", + "last": "Maier" + }, + { + "initials": "H", + "last": "Moseley" + }, + { + "initials": "S", + "last": "Zhou" + }, + { + "initials": "J", + "last": "Whitaker" + }, + { + "initials": "J", + "last": "Blalock" + } + ], + "pub_dict_key": "", + "reference_line": "Maier C, Moseley H, Zhou S, Whitaker J, Blalock J.\n \n Identification of Interactive Determinants on Idiotypic-Anti-idiotypic Antibodies through Comparison of Their Hydropathic Profiles.\n ImmunoMethods. 1994 October; 5(2):107-113. doi: 10.1006/immu.1994.1044.", + "title": "Identification of Interactive Determinants on Idiotypic-Anti-idiotypic Antibodies through Comparison of Their Hydropathic Profiles." + }, + { + "DOI": "", + "PMID": "", + "authors": [ + { + "initials": "RL", + "last": "Davies" + }, + { + "initials": "HN", + "last": "Moseley" + } + ], + "pub_dict_key": "", + "reference_line": "Davies RL, Moseley HN.\n \n Student Roots: Square root algorithm in Forth.\n Forth Dimensions. 1987; 8:8.", + "title": "Student Roots: Square root algorithm in Forth." + } +]