Joseph Kara M, Boatman Anna K, Dodds James N, Kirkwood-Donelson Kaylie I, Ryan Jack P, Zhang Jian, Thiessen Paul A, Bolton Evan E, Valdiviezo Alan, Sapozhnikova Yelena, Rusyn Ivan, Schymanski Emma L, Baker Erin S
Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Immunity, Inflammation, and Disease Laboratory, National Institute of Environmental Health Sciences, Durham, NC, 27709, USA.
Sci Data. 2025 Jan 25;12(1):150. doi: 10.1038/s41597-024-04363-0.
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.
随着人类疾病和健康问题的不断增加，关于它们与化学物质暴露之间联系的问题也持续出现，尤其是对于全氟和多氟烷基物质（PFAS）。目前，许多受关注的化学物质在用于分析评估时可获得的实验信息有限。在此，我们旨在通过为科学界提供175种PFAS及其产生的281种离子类型的多维特征来增加这方面的知识。使用一个将反相液相色谱（RPLC）、电喷雾电离（ESI）或大气压化学电离（APCI）、漂移管离子迁移谱（IMS）和质谱（MS）相结合的平台，测定了所有分析物的保留时间、碰撞截面（CCS）值和m/z比，并将其汇编成一个公开可用的多维数据集。这些信息将为科学界提供基本特征，以扩展对PFAS的分析评估，并增加用于发现新PFAS的机器学习训练集。
