Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China.
Chemosphere. 2019 Feb;217:669-679. doi: 10.1016/j.chemosphere.2018.10.200. Epub 2018 Nov 1.
In the field of computational toxicology, predicting toxicological interaction or hormesis effect of a mixture from individuals is still a challenge. The two most frequently used model concentration addition (CA) and independent action (IA) also cannot solve these challenges perfectly. In this paper, we used IDV (an interpolation method based on the Delaunay triangulation and Voronoi tessellation as well as the training set of direct equipartition ray design (EquRay) mixtures) to predict the toxicities of binary mixtures composed of hormetic ionic liquids (ILs). One of the purposes is to verify the predictive ability of IDV. The other one is to improve the risk assessment of ILs mixtures especial hormetic ILs, because the toxicity reports of ILs mixtures are rarely reported in particular the toxicity of the hormetic ILs mixtures. Hence, we determined time-dependent toxicities of four ILs and their binary mixtures (designed by EquRay) to Vibrio qinghaiensis sp.-Q67 at first. Then, mixture toxicities were predicted and compared using the IDV and CA. The results show that, the accuracy of IDV is higher than the accuracy of CA. And, more important, to some mixtures out of the CA application, IDV also can predict the mixture effects accurately. It showed that IDV can be applied to predict the toxicity of any binary mixture regardless of the type of concentration-response curve of the components. These toxicity data provided useful information for researching the prediction of hormesis or toxicological interaction of the mixture and toxicities of ILs mixtures.
在计算毒理学领域，从个体预测混合物的毒理学相互作用或激动效应仍然是一个挑战。最常使用的两种模型浓度加和（CA）和独立作用（IA）也不能完美地解决这些挑战。在本文中，我们使用 IDV（一种基于 Delaunay 三角剖分和 Voronoi 镶嵌以及直接等分射线设计（EquRay）混合物的训练集的插值方法）来预测由激动剂离子液体（ILs）组成的二元混合物的毒性。目的之一是验证 IDV 的预测能力。另一个目的是改善 ILs 混合物特别是激动剂 ILs 混合物的风险评估，因为 ILs 混合物的毒性报告很少报道，特别是激动剂 ILs 混合物的毒性报告。因此，我们首先确定了四种 ILs 及其二元混合物（由 EquRay 设计）对青海弧菌 sp.-Q67 的时变毒性。然后，使用 IDV 和 CA 预测和比较混合物毒性。结果表明，IDV 的准确性高于 CA 的准确性。更重要的是，对于 CA 应用范围之外的某些混合物，IDV 也可以准确预测混合物的效应。这表明 IDV 可以应用于预测任何二元混合物的毒性，而不受成分浓度-反应曲线类型的限制。这些毒性数据为研究混合物的激动效应或毒理学相互作用以及 ILs 混合物的毒性预测提供了有用的信息。
