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Novel approach for predicting the joint effects based on the enzyme-catalyzed kinetics.
Zheng, Min; Yao, Zhifeng; Lin, Zhifen; Fang, Shuxia; Song, Chunlei; Liu, Ying.
Afiliação
  • Zheng M; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
  • Yao Z; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
  • Lin Z; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Key Lab of Chemical Assessment and Substainability, Shanghai, China; Collaborative Innovation Center for Regional Environmental Quality,
  • Fang S; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
  • Song C; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
  • Liu Y; Shanghai Key Lab of Chemical Assessment and Substainability, Shanghai, China.
J Hazard Mater ; 307: 359-67, 2016 Apr 15.
Article em En | MEDLINE | ID: mdl-26826939
Organisms are exposed to mixtures of multiple contaminants and it is necessary to build prediction models for the joint effects, considering the high expense and the complexity of the traditional toxicity testing and the flood occurrence of environmental chemical pollutants. In this study, a new method for predicting the joint effects was developed and corresponding prediction models were constructed based on the kinetic models of enzyme-catalyzed reactions. While, we utilized Vibrio fischeri, Escherichia coli and Bacillus subtilis as model organisms and determined the chronic toxicity of the binary mixtures of sulfonamides (SAs) and sulfonamide potentiators (SAPs) (SA+SAP), the mixtures of two kinds of sulfonamides (SA+SA) and the binary mixtures of sulfonamide potentiators (SAPs) and tetracyclines (TCs) (SAP+TC) respectively. Finally, corresponding mixture toxicity data was utilized to fit and verify the prediction models for different joint effects.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Ambientais / Antibacterianos / Modelos Teóricos Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Ambientais / Antibacterianos / Modelos Teóricos Idioma: En Ano de publicação: 2016 Tipo de documento: Article