State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, PR China.
Environ Pollut. 2011 Jul;159(7):1941-7. doi: 10.1016/j.envpol.2011.03.018. Epub 2011 Apr 30.
Compound contamination and toxicity interaction necessitate the development of models that have an insight into the combined toxicity of chemicals. In this paper, a novel and simple model dependent only on the mixture information (MIM), was developed. Firstly, the concentration-response data of seven groups of binary and multi-component (pseudo-binary) mixtures with different mixture ratios to Vibrio qinghaiensis sp.-Q67 were determined using the microplate toxicity analysis. Then, a desirable non-linear function was selected to fit the data. It was found that there are good linear correlations between the location parameter (α) and mixture ratio (p) of a component and between the steepness (β) and p. Based on the correlations, a mixture toxicity model independent of pure component toxicity profiles was built. The model can be used to accurately estimate the toxicities of the seven groups of mixtures, which greatly simplified the predictive procedure of the combined toxicity.
化合物的复合污染和毒性相互作用需要开发能够深入了解化学品联合毒性的模型。本文提出了一种新颖而简单的仅依赖于混合物信息（MIM）的模型。首先，使用微孔板毒性分析方法确定了七组二元和多组分（拟二元）混合物在不同混合比下对青海弧菌 sp.-Q67 的浓度-反应数据。然后，选择合适的非线性函数对数据进行拟合。结果表明，一个组分的位置参数（α）与混合物比例（p）以及斜率（β）与 p 之间存在良好的线性相关性。基于这些相关性，建立了一个独立于纯组分毒性特征的混合物毒性模型。该模型可用于准确估计七组混合物的毒性，大大简化了联合毒性的预测过程。
