Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS)

Abstract As the occurrence of human diseases and conditions increase, questions continue to arise about their linkages to chemical exposure, especially for per-and polyfluoroalkyl substances (PFAS). Currently, many chemicals of concern have limited experimental information available for their use in...

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Main Authors: Kara M. Joseph, Anna K. Boatman, James N. Dodds, Kaylie I. Kirkwood-Donelson, Jack P. Ryan, Jian Zhang, Paul A. Thiessen, Evan E. Bolton, Alan Valdiviezo, Yelena Sapozhnikova, Ivan Rusyn, Emma L. Schymanski, Erin S. Baker
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-024-04363-0
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author Kara M. Joseph
Anna K. Boatman
James N. Dodds
Kaylie I. Kirkwood-Donelson
Jack P. Ryan
Jian Zhang
Paul A. Thiessen
Evan E. Bolton
Alan Valdiviezo
Yelena Sapozhnikova
Ivan Rusyn
Emma L. Schymanski
Erin S. Baker
author_facet Kara M. Joseph
Anna K. Boatman
James N. Dodds
Kaylie I. Kirkwood-Donelson
Jack P. Ryan
Jian Zhang
Paul A. Thiessen
Evan E. Bolton
Alan Valdiviezo
Yelena Sapozhnikova
Ivan Rusyn
Emma L. Schymanski
Erin S. Baker
author_sort Kara M. Joseph
collection DOAJ
description Abstract As the occurrence of human diseases and conditions increase, questions continue to arise about their linkages to chemical exposure, especially for per-and polyfluoroalkyl substances (PFAS). Currently, many chemicals of concern have limited experimental information available for their use in analytical assessments. Here, we aim to increase this knowledge by providing the scientific community with multidimensional characteristics for 175 PFAS and their resulting 281 ion types. Using a platform coupling reversed-phase liquid chromatography (RPLC), electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI), drift tube ion mobility spectrometry (IMS), and mass spectrometry (MS), the retention times, collision cross section (CCS) values, and m/z ratios were determined for all analytes and assembled into an openly available multidimensional dataset. This information will provide the scientific community with essential characteristics to expand analytical assessments of PFAS and augment machine learning training sets for discovering new PFAS.
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institution Kabale University
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spelling doaj-art-191ce34db0c74603a4ad41b7516d54c02025-01-26T12:15:01ZengNature PortfolioScientific Data2052-44632025-01-0112111110.1038/s41597-024-04363-0Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS)Kara M. Joseph0Anna K. Boatman1James N. Dodds2Kaylie I. Kirkwood-Donelson3Jack P. Ryan4Jian Zhang5Paul A. Thiessen6Evan E. Bolton7Alan Valdiviezo8Yelena Sapozhnikova9Ivan Rusyn10Emma L. Schymanski11Erin S. Baker12Department of Chemistry, University of North Carolina at Chapel HillDepartment of Chemistry, University of North Carolina at Chapel HillDepartment of Chemistry, University of North Carolina at Chapel HillImmunity, Inflammation, and Disease Laboratory, National Institute of Environmental Health SciencesDepartment of Chemistry, University of North Carolina at Chapel HillNational Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthNational Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthNational Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthInterdisciplinary Faculty of Toxicology, Texas A&M UniversityAgricultural Research Service, U.S Department of AgricultureInterdisciplinary Faculty of Toxicology, Texas A&M UniversityLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du SwingDepartment of Chemistry, University of North Carolina at Chapel HillAbstract As the occurrence of human diseases and conditions increase, questions continue to arise about their linkages to chemical exposure, especially for per-and polyfluoroalkyl substances (PFAS). Currently, many chemicals of concern have limited experimental information available for their use in analytical assessments. Here, we aim to increase this knowledge by providing the scientific community with multidimensional characteristics for 175 PFAS and their resulting 281 ion types. Using a platform coupling reversed-phase liquid chromatography (RPLC), electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI), drift tube ion mobility spectrometry (IMS), and mass spectrometry (MS), the retention times, collision cross section (CCS) values, and m/z ratios were determined for all analytes and assembled into an openly available multidimensional dataset. This information will provide the scientific community with essential characteristics to expand analytical assessments of PFAS and augment machine learning training sets for discovering new PFAS.https://doi.org/10.1038/s41597-024-04363-0
spellingShingle Kara M. Joseph
Anna K. Boatman
James N. Dodds
Kaylie I. Kirkwood-Donelson
Jack P. Ryan
Jian Zhang
Paul A. Thiessen
Evan E. Bolton
Alan Valdiviezo
Yelena Sapozhnikova
Ivan Rusyn
Emma L. Schymanski
Erin S. Baker
Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS)
Scientific Data
title Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS)
title_full Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS)
title_fullStr Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS)
title_full_unstemmed Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS)
title_short Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS)
title_sort multidimensional library for the improved identification of per and polyfluoroalkyl substances pfas
url https://doi.org/10.1038/s41597-024-04363-0
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