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评估真菌毒素组合的效果:哪种数学模型最合适?

Assessing the Effect of Mycotoxin Combinations: Which Mathematical Model Is (the Most) Appropriate?

机构信息

Department of Biophysics, Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovačića 1, Zagreb 10000, Croatia.

Department of Microbiology, Faculty of Pharmacy and Biochemistry, University of Zagreb, Schrottova 39, Zagreb 10000, Croatia.

出版信息

Toxins (Basel). 2020 Feb 29;12(3):153. doi: 10.3390/toxins12030153.

Abstract

In the past decades, many studies have examined the nature of the interaction between mycotoxins in biological models classifying interaction effects as antagonisms, additive effects, or synergisms based on a comparison of the observed effect with the expected effect of combination. Among several described mathematical models, the arithmetic definition of additivity and factorial analysis of variance were the most commonly used in mycotoxicology. These models are incorrectly based on the assumption that mycotoxin dose-effect curves are linear. More appropriate mathematical models for assessing mycotoxin interactions include Bliss independence, Loewe's additivity law, combination index, and isobologram analysis, Chou-Talalays median-effect approach, response surface, code for the identification of synergism numerically efficient (CISNE) and MixLow method. However, it seems that neither model is ideal. This review discusses the advantages and disadvantages of these mathematical models.

摘要

在过去的几十年中,许多研究都在生物模型中研究了霉菌毒素之间的相互作用的性质,根据观察到的作用与组合的预期作用的比较,将相互作用效果分类为拮抗作用、相加作用或协同作用。在描述的几种数学模型中,加性的算术定义和方差的析因分析是在霉菌毒素毒理学中最常用的。这些模型错误地基于霉菌毒素剂量-效应曲线是线性的假设。评估霉菌毒素相互作用的更合适的数学模型包括 Bliss 独立性、Loewe 的加性法则、组合指数和等效应线分析、Chou-Talalay 中值效应方法、响应面、协同作用的数字识别码(CISNE)和 MixLow 方法。然而,似乎没有一个模型是理想的。本综述讨论了这些数学模型的优缺点。

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