...
首页> 外文期刊>Environmental toxicology and chemistry >Generalized concentration addition approach for predicting mixture toxicity
【24h】

Generalized concentration addition approach for predicting mixture toxicity

机译:通用浓度加法预测混合物毒性

获取原文
获取原文并翻译 | 示例
           

摘要

A new mathematical model for analyzing data and predicting the effect of mixtures of toxic substances is presented as a generalized form of the concentration addition model. The proposed method, the generalized concentration addition (GCA) model, can be applied to mixtures with arbitrary strengths of interactions (synergistic or antagonistic). It requires mixture effect data for least 1 exposure concentration of the mixture in which fractions of all components and concentration-response functions for each component are known. The GCA model evaluates the interaction between components by introducing a novel response function, which is independent of the response functions for each individual components, to describe the effect of addition between different components. The GCA method was applied to published mixture toxicity data, and it was found to fit the mixture effect better than both the concentration addition model and the independent action model, the implication being that the proposed approach is widely applicable. Environ Toxicol Chem 2017;36:265-275. (c) 2016 SETAC
机译:作为浓度添加模型的通用形式,提出了一种用于分析数据和预测有毒物质混合物影响的新数学模型。所提出的方法,广义浓度加和(GCA)模型,可以应用于具有任意相互作用强度(协同或拮抗)的混合物。它要求混合物的至少一种暴露浓度的混合物效应数据,其中所有组分的分数和每种组分的浓度响应函数是已知的。 GCA模型通过引入新颖的响应函数来评估组件之间的交互,该函数独立于每个单独组件的响应函数,以描述不同组件之间添加的效果。将GCA方法应用于已公开的混合物毒性数据,发现该方法比浓度添加模型和独立作用模型均更适合混合效果,这表明该方法具有广泛的适用性。 Environ Toxicol Chem 2017; 36:265-275。 (c)2016年SETAC

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号