Literature DB >> 33965444

Arsenic toxicokinetic modeling and risk analysis: Progress, needs and applications.

Elaina M Kenyon1.   

Abstract

Arsenic (As) poses unique challenges in PBTK model development and risk analysis applications. Arsenic metabolism is complex, adequate information to attribute specific metabolites to particular adverse effects in humans is sparse, and measurement of relevant metabolites in biological media can be difficult. Multiple As PBTK models have been published and used or adapted for use in various exposure and risk analysis applications. These applications illustrate the broad utility of PBTK models for exposure and dose-response analysis, particularly for arsenic where multi-pathway, multi-route exposures and multiple toxic effects are of concern. Arsenic PBTK models have been used together with exposure reconstruction and dose-response functions to estimate risk of specific adverse health effects due to drinking water exposure and consumption of specific foodstuffs (e.g. rice, seafood), as well as to derive safe exposure levels and develop consumption advisories. Future refinements to arsenic PBTK models can enhance the confidence in such analyses. Improved estimates for methylation biotransformation parameters based on in vitro to in vivo extrapolation (IVIVE) methods and estimation of interindividual variability in key model parameters for specific toxicologically relevant metabolites are two important areas for consideration. Published by Elsevier B.V.

Entities:  

Keywords:  Arsenic; Risk analysis; Toxicokinetics; pbtk modeling

Mesh:

Substances:

Year:  2021        PMID: 33965444      PMCID: PMC8522349          DOI: 10.1016/j.tox.2021.152809

Source DB:  PubMed          Journal:  Toxicology        ISSN: 0300-483X            Impact factor:   4.571


  74 in total

Review 1.  Metabolism of arsenic in human liver: the role of membrane transporters.

Authors:  Zuzana Drobná; Felecia S Walton; David S Paul; Weibing Xing; David J Thomas; Miroslav Stýblo
Journal:  Arch Toxicol       Date:  2009-12-18       Impact factor: 5.153

Review 2.  AS3MT, GSTO, and PNP polymorphisms: impact on arsenic methylation and implications for disease susceptibility.

Authors:  Ray Antonelli; Kan Shao; David J Thomas; Reeder Sams; John Cowden
Journal:  Environ Res       Date:  2014-05-08       Impact factor: 6.498

Review 3.  Metabolism and toxicity of arsenicals in mammals.

Authors:  Adeel Sattar; Shuyu Xie; Mian Abdul Hafeez; Xu Wang; Hafiz Iftikhar Hussain; Zahid Iqbal; Yuanhu Pan; Mujahid Iqbal; Muhammad Abubakr Shabbir; Zonghui Yuan
Journal:  Environ Toxicol Pharmacol       Date:  2016-11-03       Impact factor: 4.860

4.  Effect of dietary treatment with dimethylarsinous acid (DMA(III)) on the urinary bladder epithelium of arsenic (+3 oxidation state) methyltransferase (As3mt) knockout and C57BL/6 wild type female mice.

Authors:  Puttappa R Dodmane; Lora L Arnold; Karen L Pennington; David J Thomas; Samuel M Cohen
Journal:  Toxicology       Date:  2013-01-30       Impact factor: 4.221

5.  Reduction and binding of arsenate and dimethylarsinate by glutathione: a magnetic resonance study.

Authors:  M Delnomdedieu; M M Basti; J D Otvos; D J Thomas
Journal:  Chem Biol Interact       Date:  1994-02       Impact factor: 5.192

Review 6.  In vitro measurements of metabolism for application in pharmacokinetic modeling.

Authors:  John C Lipscomb; Torka S Poet
Journal:  Pharmacol Ther       Date:  2008-02-15       Impact factor: 12.310

Review 7.  The role of arsenic in obesity and diabetes.

Authors:  Tahereh Farkhondeh; Saeed Samarghandian; Mohsen Azimi-Nezhad
Journal:  J Cell Physiol       Date:  2019-01-22       Impact factor: 6.384

8.  Mathematical model of uptake and metabolism of arsenic(III) in human hepatocytes - Incorporation of cellular antioxidant response and threshold-dependent behavior.

Authors:  Spyros K Stamatelos; Christopher J Brinkerhoff; Sastry S Isukapalli; Panos G Georgopoulos
Journal:  BMC Syst Biol       Date:  2011-01-25

9.  Mathematical modeling of the effects of glutathione on arsenic methylation.

Authors:  Sean D Lawley; Jina Yun; Mary V Gamble; Megan N Hall; Michael C Reed; H Frederik Nijhout
Journal:  Theor Biol Med Model       Date:  2014-05-16       Impact factor: 2.432

10.  Reorientation of the Methyl Group in MAs(III) is the Rate-Limiting Step in the ArsM As(III) S-Adenosylmethionine Methyltransferase Reaction.

Authors:  Charles Packianathan; Jiaojiao Li; Palani Kandavelu; Banumathi Sankaran; Barry P Rosen
Journal:  ACS Omega       Date:  2018-03-14
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