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Per- and polyfluoroalkyl substances (PFAS) are a class of man-made chemicals of global concern for many health and regulatory agencies due to their widespread use and persistence in the environment (in soil, air, and water), bioaccumulation, and toxicity. This concern has catalyzed a need to aggregate data to support research efforts that can, in turn, inform regulatory and statutory actions. An ongoing challenge regarding PFAS has been the shifting definition of what qualifies a substance to be a member of the PFAS class. There is no single definition for a PFAS, but various attempts have been made to utilize substructural definitions that either encompass broad working scopes or satisfy narrower regulatory guidelines. Depending on the size and specificity of PFAS substructural filters applied to the U.S. Environmental Protection Agency (EPA) DSSTox database, currently exceeding 900,000 unique substances, PFAS substructure-defined space can span hundreds to tens of thousands of compounds. This manuscript reports on the curation of PFAS chemicals and assembly of lists that have been made publicly available to the community via the EPA’s CompTox Chemicals Dashboard. Creation of these PFAS lists required the harvesting of data from EPA and online databases, peer-reviewed publications, and regulatory documents. These data have been extracted and manually curated, annotated with structures, and made available to the community in the form of lists defined by structure filters, as well as lists comprising non-structurable PFAS, such as polymers and complex mixtures. These lists, along with their associated linkages to predicted and measured data, are fueling PFAS research efforts within the EPA and are serving as a valuable resource to the international scientific community.

Although urinary 1,6-hexamethylene diamine (HDA) is a useful biomarker of exposure to 1,6-hexamethylene diisocyanate (HDI), a large degree of unexplained intra- and inter-individual variability exists between estimated HDI exposure and urine HDA levels. We investigated the effect of individual and workplace factors on urine HDA levels using quantitative dermal and inhalation exposure data derived from a survey of automotive spray painters exposed to HDI. Painters' dermal and breathing-zone HDI-exposures were monitored over an entire workday for up to three separate workdays, spaced approximately one month apart. One urine sample was collected before the start of work with HDI-containing paints, and multiple samples were collected throughout the workday. Using mixed effects multiple linear regression modeling, coverall use resulted in significantly lower HDA levels (p= 0.12), and weekday contributed to significant variability in HDA levels (p= 0.056). We also investigated differences in urine HDA levels stratified by dichotomous and classification covariates using analysis of variance. Use of coveralls (p= 0.05), respirator type worn (p= 0.06), smoker status (p= 0.12), paint-booth type (p= 0.02), and more than one painter at the shop (p= 0.10) were all found to significantly affect urine HDA levels adjusted for creatinine concentration. Coverall use remained significant (p= 0.10), even after adjusting for respirator type. These results indicate that the variation in urine HDA level is mainly due to workplace factors and that appropriate dermal and inhalation protection is required to prevent HDI exposure. [ABSTRACT FROM AUTHOR]