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.
Sci Rep. 2017 Mar 13;7:43473. doi: 10.1038/srep43473.
Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDV. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDV successfully predicted the toxicities of various types of binary mixtures.
浓度加和（CA）被提议作为化学混合物生态风险评估的一种合理默认方法。然而，如果不是所有成分在给定的效应下都有明确的有效浓度，例如某些化合物会引起激素作用，那么 CA 不能预测混合物在某些效应区的毒性。在本文中，我们开发了一种用于预测各种类型二元混合物毒性的新方法，即基于 Delaunay 三角剖分（DT）和 Voronoi 图（VT）以及直接等分射线设计（EquRay）混合物训练集的插值方法，简称 IDV。首先，采用 EquRay 设计五条二元混合物射线的基本浓度组成。通过时间依赖微板毒性分析测定了单一组分和混合物射线在不同时间和不同浓度下的毒性效应。其次，将纯组分和各种混合物射线的浓度-毒性数据作为训练集。通过训练集中浓度的各种顶点构建 DT 三角形和 VT 多边形。通过顶点的线性插值和自然邻域插值来预测未知混合物的毒性。IDV 成功地预测了各种类型二元混合物的毒性。
