Literature DB >> 21769654

Application of the similarity parameter (λ) to prediction of the joint effects of nonequitoxic mixtures.

Dayong Tian1, Zhifen Lin, Jianqing Ding, Daqiang Yin, Yalei Zhang.   

Abstract

Although environmental contaminants are usually encountered as nonequitoxic mixtures, most studies have investigated the toxicity of equitoxic mixtures. In the present study, a method for prediction of the toxicity of nonequitoxic mixtures was developed using the similarity parameter (λ). The joint effect of multiple contaminants at the median inhibition concentration in equitoxic ([Formula: see text]) and nonequitoxic ([Formula: see text]) binary, ternary, and quaternary mixtures was investigated using Vibrio fischeri. The observed results indicate that the concentration ratios of individual chemicals in the mixtures influenced the joint effects, and that λ could be employed to evaluate the relation between [Formula: see text] and [Formula: see text]. Prediction models for the joint effects of nonequitoxic ([Formula: see text]) mixtures were derived from a combination of [Formula: see text] and λ. The predictive capabilities of these models were validated by comparing the predicted data with the observed data for binary, ternary, and quaternary mixtures. The prediction models have promising applications in controlling environmental pollution, evaluating drug interactions, and optimizing combinations of pesticides used in agriculture.

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Year:  2011        PMID: 21769654     DOI: 10.1007/s00244-011-9695-6

Source DB:  PubMed          Journal:  Arch Environ Contam Toxicol        ISSN: 0090-4341            Impact factor:   2.804


  2 in total

Review 1.  Additivity and Interactions in Ecotoxicity of Pollutant Mixtures: Some Patterns, Conclusions, and Open Questions.

Authors:  Ismael Rodea-Palomares; Miguel González-Pleiter; Keila Martín-Betancor; Roberto Rosal; Francisca Fernández-Piñas
Journal:  Toxics       Date:  2015-09-25

2.  Prediction of the Toxicity of Binary Mixtures by QSAR Approach Using the Hypothetical Descriptors.

Authors:  Ting Wang; Lili Tang; Feng Luan; M Natália D S Cordeiro
Journal:  Int J Mol Sci       Date:  2018-10-31       Impact factor: 5.923

  2 in total

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