Assessing the Effect of Mycotoxin Combinations: Which Mathematical Model Is (the Most) Appropriate?
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Department of Biophysics, Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovačića 1, Zagreb 10000, Croatia
2
Department of Microbiology, Faculty of Pharmacy and Biochemistry, University of Zagreb, Schrottova 39, Zagreb 10000, Croatia
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Author to whom correspondence should be addressed.
Toxins 2020, 12(3), 153; https://doi.org/10.3390/toxins12030153 (registering DOI)
Received: 8 January 2020 / Revised: 17 February 2020 / Accepted: 26 February 2020 / Published: 29 February 2020
(This article belongs to the Special Issue Toxicological Effects of Mycotoxin on Target Cells)
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.
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Keywords:
mycotoxin interaction; Loewe additivity; combination index; isobologram; Chou-Talalay method; MixLow
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MDPI and ACS Style
Kifer, D.; Jakšić, D.; Šegvić Klarić, M. Assessing the Effect of Mycotoxin Combinations: Which Mathematical Model Is (the Most) Appropriate? Toxins 2020, 12, 153.
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