Novel full logistic model for estimation of the estrogenic activity of chemical mixtures
Novel full logistic model for estimation of the estrogenic activity of chemical mixtures
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DOI：
10.1016/j.tox.2016.06.017
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发表时间：
2016-06-01
期刊：
影响因子：
4.5
通讯作者：
Cajthaml, Tomas
中科院分区：
文献类型：
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作者：
Ezechias, Martin;Cajthaml, Tomas
雌激素化合物以及其他生物活性物质通常以复杂混合物的形式存在于环境中。仍然没有令人满意的模型，将能够预测的毒性作用的混合物含有部分受体激动剂和化合物的剂量-反应曲线的不同参数。因此，一种新的全逻辑模型（FLM）的预测使用的剂量-反应曲线的所有参数已被建议，并与以前公布的方法进行比较。我们使用酵母报告基因测定和人T47 D细胞系测试了所选雌激素的受体结合活性，包括完全和部分激动剂及其混合物。组合效应与FLM建模和预测曲线与实验获得的数据进行了比较。FLM产生了一个很好的适合从两个受体结合试验的实验数据，并给出了更好的预测比以前发表的方法。FLM还提供了有关最终部分激动剂剂量-反应曲线的令人满意的结果，其中最大值受到部分激动剂抑制作用的影响。FLM不受任何简化的限制，如毒性当量因子法或广义浓度相加法，因此它可以用于含有不同剂量-反应曲线参数（最大值、最小值、拐点或斜率）的化学品的混合物。(C)由Elsevier爱尔兰Ltd.出版
Estrogenic compounds as well as other biologically active substances are commonly present in the form of complex mixtures in the environment. There is still no satisfactory model that would be capable of predicting the toxic effects of mixtures containing partial receptor agonists and compounds with different parameters of their dose-response curves. Therefore, a novel Full Logistic Model (FLM) of prediction using all the parameters of dose-response curves has been suggested and compared with previously published approaches. We tested the receptor-binding activities of selected estrogens including full and partial agonists and their mixtures using yeast reporter gene assays and the human T47D cell line. Combination effects were modeled with FLM and predicted curves were compared with the data obtained experimentally. FLM yielded a good fit to the experimental data from both the receptor binding assays and gave better predictions than the previously published approaches. FLM also provided satisfactory results regarding final partial agonistic dose-response curves with maximum influenced by the inhibitory effect of the partial agonist. FLM is not limited by any simplification like the toxic equivalency factor approach or generalized concentration addition and therefore it could be employed for mixtures containing chemicals with different parameters of their dose-response curves (maximum, minimum, inflex point or slope). (C) 2016 Published by Elsevier Ireland Ltd.