Better Understanding Exposures to PAHs and Pesticides
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2017/04/20
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By Smith JN
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Description:We use in vitro metabolism and activity based protein profiling to understand Polycyclic Aromatic Hydrocarbon (PAH) metabolism, how PAHs and life-stages may change the amount of enzymes that metabolize PAHs, and how different PAHs may affect the metabolism of other PAHs. We have used these measurements to develop, validate, and refine the first suite of predictive computational dosimetry models (physiologically based pharmacokinetic, or PBPK, models) for PAHs. These models incorporate species and life stage differences in anatomy, physiology, and key biological processes associated with PAH absorption, tissue distribution and interactions, metabolism, and excretion. We dosed humans with very small amounts of 14C-PAHs to collect pharmacokinetic data and compared the results to our models. These PBPK models are designed to predict target tissue doses of PAHs and their metabolites that may cause toxicity or cancer. These PBPK models can be useful for simulating biomarker levels (i.e. contaminant parent and metabolite levels in various compartments that may be sampled for biomonitoring) and predicting an environmental exposure dose from the measured biomarker levels. We have also developed cellular and PBPK models of pesticide transport into saliva. [Description provided by NIOSH]
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Pages in Document:1
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NIOSHTIC Number:nn:20051005
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Citation:The NIEHS Superfund Research Program & NCEH/ATSDR Office of Science Seminar, April 20, 2017, Atlanta, Georga. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Agency for Toxic Substances and Disease Registry, 2017 Apr; :1
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Federal Fiscal Year:2017
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Performing Organization:Battelle Pacific Northwest Laboratory
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Peer Reviewed:False
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Start Date:20060901
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Source Full Name:The NIEHS Superfund Research Program & NCEH/ATSDR Office of Science Seminar, April 20, 2017, Atlanta, Georga
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End Date:20170831
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Main Document Checksum:urn:sha-512:bbb7de1f99f65358d934c1fbb354c61018f59c2814407f8cd759d14aa70ca5f53a95211ee35c054cef7462ac62b4507d27c3f3f08b2a49a4dfe48d4c6e1b4e5c
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