The utility of alternative models in particulate matter air pollution toxicology

被引:3
|
作者
Smoot, Jacob [1 ]
Padilla, Stephanie [2 ]
Farraj, Aimen K. [3 ]
机构
[1] Oak Ridge Inst Sci & Educ, Oak Ridge, TN USA
[2] US EPA, Ctr Computat Toxicol & Exposure, Biomol & Computat Toxicol Div, RTP, Durham, NC USA
[3] US EPA, Publ Hlth & Integrated Toxicol Div, RTP, Durham, NC 27709 USA
来源
关键词
Alternative models; Particulate matter; Toxicity; Zebrafish; Drosophila melanogaster; C; elegans; D; rerio; LONG-TERM EXPOSURE; CAENORHABDITIS-ELEGANS; OXIDATIVE STRESS; ORGANIC EXTRACTS; DROSOPHILA-MELANOGASTER; DEVELOPMENTAL TOXICITY; AMBIENT PM2.5; DANIO-RERIO; C; ELEGANS; LIFE-SPAN;
D O I
10.1016/j.crtox.2022.100077
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
Exposure to particulate matter (PM) air pollution increases risk of adverse human health effects. As more attention is brought to bear on the problem of PM, traditional mammalian in vivo models struggle to keep up with the risk assessment challenges posed by the countless number of unique PM samples across air sheds with limited or no toxicity information. This review examines the utility of three higher throughput, alternative, in vivo animal models in PM toxicity research: Danio rerio (zebrafish), Caenorhabditis elegans (nematode), and Drosophila melanogaster (fruit fly). These model organisms vary in basic biology, ease of handling, methods of exposure to PM, number and types of available assays, and the degree to which they mirror human biology and responsiveness, among other differences. The use of these models in PM research dates back over a decade, with assessments of the toxicity of various PM sources including traffic-related combustion emissions, wildland fire smoke, and coal fly ash. This article reviews the use of these alternative model organisms in PM toxicity studies, their biology, the various assays developed, endpoints measured, their strengths and limitations, as well as their potential role in PM toxicity assessment and mechanistic research going forward.
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收藏
页数:11
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