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DOI | 10.1021/acs.est.6b06230 |
Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology | |
Conolly, Rory B.1; Ankley, Gerald T.2; Cheng, WanYun1; Mayo, Michael L.3; Miller, David H.4; Perkins, Edward J.3; Villeneuve, Daniel L.2; Watanabe, Karen H.5 | |
发表日期 | 2017-04-18 |
ISSN | 0013-936X |
卷号 | 51期号:8页码:4661-4672 |
英文摘要 | A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose response, and time-course predictions that can support regulatory decision-making: Herein we describe several facets of qAOPs, including (a) motivation for development, (b) technical considerations, (c) evaluation of confidence, and (d) potential applications. The qAOP used as an illustrative example for these points describe the linkage between inhibition of cytochrome P450 19A aromatase (the MIE) and population-level decreases in the fathead minnow (FHM; Pimephales promelas). The qAOP consists of three linked computational models for the following: (a) the hypothalamic-pitutitary-gonadal axis in female FHMs, where aromatase inhibition decreases the conversion of testosterone to 17 beta-esttadiol (E2), thereby reducing E2-dependent vitellogenin (VTG; egg yolk protein precursor) synthesis, (b) VTG-dependent egg development and spawning (fecundity), and (c) fecundity-dependent population trajectory. While development of the example qAQP was based on experiments with FHMs exposed to the aromatase inhibitor fadrozole, we also show how a toxic equivalence (TEQ) calculation allows use of the qAOP to predict effects of another, untested aromatase inhibitor, iprodione. While qAOP development can be resource-intensive, the quantitative predictions obtained, and TEQ-based application-to multiple chemicals, may be sufficient to justify the cost for some, applications in regulatory decision-making. |
语种 | 英语 |
WOS记录号 | WOS:000399859700057 |
来源期刊 | ENVIRONMENTAL SCIENCE & TECHNOLOGY
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来源机构 | 美国环保署 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/60452 |
作者单位 | 1.US Environm Protect Agcy, Off Res & Dev, Natl Hlth & Environm Effects Res Lab, Integrated Syst Toxicol Div, Res Triangle Pk, NC 27709 USA; 2.US Environm Protect Agcy, Off Res & Dev, Natl Hlth & Environm Effects Res Lab, Mid Continent Ecol Div, Duluth, MN 55804 USA; 3.US Army Engn Res & Dev Ctr, Environm Lab, Vicksburg, MS 39180 USA; 4.US Environm Protect Agcy, Off Res & Dev, Natl Hlth & Environm Effects Res Lab, Mid Continent Ecol Div, Grosse Isle, MI 48138 USA; 5.Arizona State Univ, Sch Math & Nat Sci, West Campus, Glendale, AZ 85306 USA |
推荐引用方式 GB/T 7714 | Conolly, Rory B.,Ankley, Gerald T.,Cheng, WanYun,et al. Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology[J]. 美国环保署,2017,51(8):4661-4672. |
APA | Conolly, Rory B..,Ankley, Gerald T..,Cheng, WanYun.,Mayo, Michael L..,Miller, David H..,...&Watanabe, Karen H..(2017).Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology.ENVIRONMENTAL SCIENCE & TECHNOLOGY,51(8),4661-4672. |
MLA | Conolly, Rory B.,et al."Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology".ENVIRONMENTAL SCIENCE & TECHNOLOGY 51.8(2017):4661-4672. |
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