Modeling chemical bioaccumulation in snakes, part 1: Model development

IF 3.1 Q2 TOXICOLOGY
Xiaoyu Zhang, Zijian Li
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引用次数: 0

Abstract

Environmental chemical emission influences ecological health to some extent. Predators (e.g., snakes) could bioaccumulate chemicals along the food chain, which also leaves potential health implications on their reproduction. For the difficulty of collecting related biomatrices for exposure assessment, part 1 of this study proposed a modeling method relying on physiologically based kinetic (PBK) theory to estimate snake chronic exposure to environmental chemicals. In the steady state, the biotransfer factors of chemicals produced by the PBK model can indicate a snake’s chronic internal exposure to environmental chemicals and their potential for bioaccumulation at this level of the food web. Specifically, 3074 organic chemicals were compelled into the dataset for PBK modeling (part 2 of the study). The modeling framework covered the physiological process of the skin to consider shed snakeskin as a potential biomarker for future study. The proposed modeling approach was integrated into a spreadsheet, enabling the modification of input values to simulate outcomes for a wide range of chemical and snake species. The proposed model can help assess the ecological risks of environmental chemicals and quantify their behavior in the food web.
蛇类体内化学品生物累积模型,第 1 部分:模型开发
环境中的化学品排放会在一定程度上影响生态健康。捕食者(如蛇类)可能会沿着食物链对化学物质进行生物累积,这也会对其生殖健康造成潜在影响。由于难以收集相关的生物矩阵来进行暴露评估,本研究的第一部分提出了一种基于生理动力学(PBK)理论的建模方法来估算蛇对环境化学物质的慢性暴露。在稳定状态下,PBK 模型产生的化学物质生物转移因子可以显示蛇在体内长期接触环境化学物质的情况,以及这些化学物质在食物网这一层次的生物累积潜力。具体来说,有 3074 种有机化学物质被纳入了 PBK 模型的数据集中(研究的第二部分)。建模框架涵盖了皮肤的生理过程,以考虑将脱落的蛇皮作为未来研究的潜在生物标志物。建议的建模方法已集成到电子表格中,可修改输入值以模拟各种化学品和蛇类的结果。建议的模型有助于评估环境化学物质的生态风险,并量化其在食物网中的行为。
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来源期刊
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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