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新兴关注污染物对日本三角涡虫的毒性:定量构效关系模型与大型溞的毒性关系。

Toxicity of contaminants of emerging concern to Dugesia japonica: QSTR modeling and toxicity relationship with Daphnia magna.

机构信息

Boğaziçi University, Institute of Environmental Sciences, Ecotoxicology and Chemometrics Lab, Hisar Campus, Bebek, 34342 Istanbul, Turkey.

Boğaziçi University, Institute of Environmental Sciences, Ecotoxicology and Chemometrics Lab, Hisar Campus, Bebek, 34342 Istanbul, Turkey.

出版信息

J Hazard Mater. 2018 Jun 5;351:20-28. doi: 10.1016/j.jhazmat.2018.02.046. Epub 2018 Feb 24.

Abstract

Freshwater planarian Dugesia japonica has a critical ecological importance owing to its unique properties. This study presents for the first time an in silico approach to determine a priori the acute toxicity of contaminants of emerging concern towards D. japonica. Quantitative structure-toxicity/toxicity-toxicity relationship (QSTR/QTTR) models provided here allow producing reliable information using the existing data, thus, reducing the demand of in vivo and in vitro experiments, and contributing to the need for a more holistic approach to environmental safety assessment. Both models are promising for being notably simple and robust, meeting rigorous validation metrics and the OECD criteria. The QTTR model based on the available Daphnia magna data might also contribute to the US EPA Interspecies Correlation Estimation web application. Moreover, the proposed models were applied on hundreds of environmentally significant chemicals lacking experimental D. japonica toxicity data and predicted toxicity values were reported for the first time. The models presented here can be used as potential tools in toxicity assessment, screening and prioritization of chemicals and development of risk management measures in a scientific and regulatory frame.

摘要

淡水涡虫日本有重要的生态意义,因为它具有独特的性质。本研究首次提出了一种计算方法,以预测新兴关注污染物对日本涡虫的急性毒性。这里提供的定量结构-毒性/毒性-毒性关系 (QSTR/QTTR) 模型允许使用现有数据生成可靠的信息,从而减少对体内和体外实验的需求,并有助于对环境安全评估采用更全面的方法。这两种模型都很有前途,因为它们非常简单和稳健,符合严格的验证指标和经合组织的标准。基于现有水蚤数据的 QTTR 模型也可能有助于美国环保署物种间相关性估算网络应用程序。此外,还将所提出的模型应用于数百种具有环境意义的化学品,这些化学品缺乏实验性日本涡虫毒性数据,并首次报告了预测的毒性值。这里提出的模型可作为毒性评估、化学品筛选和优先级排序以及在科学和监管框架内制定风险管理措施的潜在工具。

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