Lambert Ronald J W, Dawson Douglas A
Dept. Science Sharnbrook Academy , Sharnbrook , Bedfordshire , UK . Email:
Department of Biology/Toxicology , Ashland University , Ashland , OH 44805 , USA.
Toxicol Res (Camb). 2019 Apr 1;8(4):509-521. doi: 10.1039/c9tx00005d. eCollection 2019 Jul 1.
Time-dependent toxicity data of specific toxicants observed against were analysed using a single time-dependent Weibull cumulative distribution function (CDF). For binary mixtures the individual Weibull parameters provided the marginals for a bivariate copula model, characterised by a single extra parameter, the interaction exponent, . The copula model unites both the dose addition (DA, Loewe additivity) and dose independence (DI, Bliss independence) hypotheses of combinations into a single explicit equation and returns both hypotheses as special cases. The model predicts the linear isoboles from sham (like against like) experiments and the linear, concave, convex and mixed concave-convex isoboles from true binary mixtures. Systems are defined as being independent when = 1, additive when min( , ) ≤ ≤ max( , ), antagonistic when < min( , ) and synergistic when > max( , ), where are the individual dose (concentration) exponents. More complex mixtures were analysed by developing -dimensional copulas: two ternary systems were analysed using a ternary copula that returned the three bivariate marginals and the three individual marginals of the mixture. The general model can also be used for time-independent studies by simply removing the time dependency. Research into combined effects has often assumed that if both the parameters for all the individual components in a mixture and the model for combinations were known then the additive effect of the whole could be predicted. This hypothesis has been shown to be false because without knowing how the components in a mixture interact the predictions from the standard DI or DA models provide only an initial, best guess, analysis.
针对特定毒物观察到的时间依赖性毒性数据,使用单个时间依赖性威布尔累积分布函数(CDF)进行分析。对于二元混合物,各个威布尔参数为二元copula模型提供了边缘分布,该模型由一个额外的参数即相互作用指数来表征。copula模型将组合的剂量相加(DA,洛维相加性)和剂量独立性(DI,布利斯独立性)假设统一到一个单一的显式方程中,并将这两个假设作为特殊情况返回。该模型预测假实验(如同类对照)中的线性等效线图以及真实二元混合物中的线性、凹形、凸形和混合凹-凸等效线图。当 = 1时,系统被定义为独立;当min(, ) ≤ ≤ max(, )时为相加;当 < min(, )时为拮抗;当 > max(, )时为协同,其中 是各个剂量(浓度)指数。通过开发 - 维copula来分析更复杂的混合物:使用三元copula分析了两个三元系统,该三元copula返回混合物的三个二元边缘分布和三个个体边缘分布。通过简单地去除时间依赖性,通用模型也可用于与时间无关的研究。对联合效应的研究常常假设,如果混合物中所有单个成分的参数以及组合模型都已知,那么整个混合物的相加效应就可以预测。但这个假设已被证明是错误的,因为在不知道混合物中的成分如何相互作用的情况下,标准DI或DA模型的预测仅提供了初步的、最佳猜测性的分析。