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Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review

Developments in industrial applications inevitably accelerate the discharge of enormous substances into the environment, whereas multi-component mixtures commonly cause joint toxicity which is distinct from the simple sum of independent effect. Thus, ecotoxicological assessment, by luminescent bioas...

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Autores principales: Wang, Dan, Wang, Shan, Bai, Linming, Nasir, Muhammad Salman, Li, Shanshan, Yan, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412757/
https://www.ncbi.nlm.nih.gov/pubmed/32849340
http://dx.doi.org/10.3389/fmicb.2020.01651
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author Wang, Dan
Wang, Shan
Bai, Linming
Nasir, Muhammad Salman
Li, Shanshan
Yan, Wei
author_facet Wang, Dan
Wang, Shan
Bai, Linming
Nasir, Muhammad Salman
Li, Shanshan
Yan, Wei
author_sort Wang, Dan
collection PubMed
description Developments in industrial applications inevitably accelerate the discharge of enormous substances into the environment, whereas multi-component mixtures commonly cause joint toxicity which is distinct from the simple sum of independent effect. Thus, ecotoxicological assessment, by luminescent bioassays has recently brought increasing attention to overcome the environmental risks. Based on the above viewpoint, this review included a brief introduction to the occurrence and characteristics of toxic bioassay based on the luminescent bacteria. In order to assess the environmental risk of mixtures, a series of models for the prediction of the joint effect of multi-component mixtures have been summarized and discussed in-depth. Among them, Quantitative Structure-Activity Relationship (QSAR) method which was widely applied in silico has been described in detail. Furthermore, the reported potential mechanisms of joint toxicity on the luminescent bacteria were also overviewed, including the Trojan-horse type mechanism, funnel hypothesis, and fishing hypothesis. The future perspectives toward the development and application of toxicity assessment based on luminescent bacteria were proposed.
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spelling pubmed-74127572020-08-25 Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review Wang, Dan Wang, Shan Bai, Linming Nasir, Muhammad Salman Li, Shanshan Yan, Wei Front Microbiol Microbiology Developments in industrial applications inevitably accelerate the discharge of enormous substances into the environment, whereas multi-component mixtures commonly cause joint toxicity which is distinct from the simple sum of independent effect. Thus, ecotoxicological assessment, by luminescent bioassays has recently brought increasing attention to overcome the environmental risks. Based on the above viewpoint, this review included a brief introduction to the occurrence and characteristics of toxic bioassay based on the luminescent bacteria. In order to assess the environmental risk of mixtures, a series of models for the prediction of the joint effect of multi-component mixtures have been summarized and discussed in-depth. Among them, Quantitative Structure-Activity Relationship (QSAR) method which was widely applied in silico has been described in detail. Furthermore, the reported potential mechanisms of joint toxicity on the luminescent bacteria were also overviewed, including the Trojan-horse type mechanism, funnel hypothesis, and fishing hypothesis. The future perspectives toward the development and application of toxicity assessment based on luminescent bacteria were proposed. Frontiers Media S.A. 2020-07-31 /pmc/articles/PMC7412757/ /pubmed/32849340 http://dx.doi.org/10.3389/fmicb.2020.01651 Text en Copyright © 2020 Wang, Wang, Bai, Nasir, Li and Yan. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Wang, Dan
Wang, Shan
Bai, Linming
Nasir, Muhammad Salman
Li, Shanshan
Yan, Wei
Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review
title Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review
title_full Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review
title_fullStr Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review
title_full_unstemmed Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review
title_short Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review
title_sort mathematical modeling approaches for assessing the joint toxicity of chemical mixtures based on luminescent bacteria: a systematic review
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412757/
https://www.ncbi.nlm.nih.gov/pubmed/32849340
http://dx.doi.org/10.3389/fmicb.2020.01651
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