将金属特异化数据纳入QICAR模型,并应用于数据贫乏的技术关键元素
Séverine Le Faucheur1, Jelle Mertens2, Eric Van Genderen3
1Université de Pau et des Pays de l'Adour, Centre national de la recherche scientifique (CNRS), Institut des sciences analytiques et de physico-chimie pour l'environnement et les matériaux (IPREM), Pau, France.
Environmental toxicology and chemistry
|September 19, 2025
概括
定量离子特征-活性关系 (QICARs) 预测金属毒性. 使用金属特异化改进了一些金属的预测,但由于复杂的特异化,揭示了技术关键元素的局限性,这表明自由离子活性可能不足.
科学领域:
- 环境化学环境化学
- 生态毒理学 生态毒理学
- 计算化学计算化学
背景情况:
- 量化离子特性-活性关系 (QICARs) 之前将金属特性与水生物质的毒性联系在一起.
- 这些模型最初是为数据丰富的元素开发的,并应用于技术关键元素 (TCE).
研究的目的:
- 通过结合计算的金属特异化来扩展QICAR,以改善毒性预测.
- 为了评估自由金属离子活性与总溶解金属度的预测能力.
- 调查TCE的毒性,特别是那些具有复杂物种的物种.
主要方法:
- 利用线性自由能量关系来估计热力学常数.
- 计算的金属物种化和表达的毒性终点作为自由金属活动.
- 进行了回归分析,使用共价指数 (日志转换 χm2r) 作为预测值.
主要成果:
- 整合金属特异化略有改善了训练金属的回归确定系数.
- 共价指数仍然是训练金属急性毒性的最佳预测指标.
- 对TCE的回归显著较差,特别是在非常低的自由金属离子度 (<10-18M) 时.
结论:
- 对于TCEs来说,其表现不佳的原因是它们的特异性物种化,以中性多氧物种为主.
- QICARs仍然很有价值,但这项研究强调,单独的自由离子活性可能不足以预测具有复杂特异性的金属的毒性.
- 这表明当前模型对具有复杂环境化学成分的数据较差的金属存在局限性.
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