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亚致死效应建模在化学品环境风险评估中的应用:问题定义、模型变体、应用和挑战。

Sublethal effect modelling for environmental risk assessment of chemicals: Problem definition, model variants, application and challenges.

机构信息

Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, United Kingdom.

Syngenta Crop Protection, LLC, Greensboro, NC, United States of America.

出版信息

Sci Total Environ. 2020 Nov 25;745:141027. doi: 10.1016/j.scitotenv.2020.141027. Epub 2020 Jul 21.

Abstract

Bioenergetic models, and specifically dynamic energy budget (DEB) theory, are gathering a great deal of interest as a tool to predict the effects of realistically variable exposure to toxicants over time on an individual animal. Here we use aquatic ecological risk assessment (ERA) as the context for a review of the different model variants within DEB and the closely related DEBkiss theory (incl. reserves, ageing, size & maturity, starvation). We propose a coherent and unifying naming scheme for all current major DEB variants, explore the implications of each model's underlying assumptions in terms of its capability and complexity and analyse differences between the models (endpoints, mathematical differences, physiological modes of action). The results imply a hierarchy of model complexity which could be used to guide the implementation of simplified model variants. We provide a decision tree to support matching the simplest suitable model to a given research or regulatory question. We detail which new insights can be gained by using DEB in toxicokinetic-toxicodynamic modelling, both generally and for the specific example of ERA, and highlight open questions. Specifically, we outline a moving time window approach to assess time-variable exposure concentrations and discuss how to account for cross-generational exposure. Where possible, we suggest valuable topics for experimental and theoretical research.

摘要

生物能量学模型,特别是动态能量预算(DEB)理论,作为一种工具,越来越受到关注,可以预测个体动物在实际变化的暴露于毒物环境中的长期影响。在这里,我们将水生生态风险评估(ERA)作为背景,综述 DEB 及其密切相关的 DEBkiss 理论(包括储备、衰老、大小和成熟度、饥饿)内的不同模型变体。我们为所有当前主要的 DEB 变体提出了一个连贯统一的命名方案,探讨了每个模型的基本假设在其能力和复杂性方面的含义,并分析了模型之间的差异(终点、数学差异、生理作用模式)。结果表明,模型复杂性存在一个层次结构,可以用来指导简化模型变体的实施。我们提供了一个决策树来支持根据给定的研究或监管问题选择最简单适用的模型。我们详细介绍了在毒代动力学-毒效动力学建模中使用 DEB 可以获得哪些新的见解,包括一般情况和 ERA 的具体示例,并强调了一些开放性问题。具体来说,我们概述了一种移动时间窗口方法来评估时变暴露浓度,并讨论了如何考虑跨代暴露。在可能的情况下,我们为实验和理论研究提出了有价值的主题。

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