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Toxicol In Vitro. 2018 Feb;46:294-303. doi: 10.1016/j.tiv.2017.10.022. Epub 2017 Oct 21.

Generalized concentration addition accurately predicts estrogenic potentials of mixtures and environmental samples containing partial agonists.

Author information

1
School of Environment & Sustainability and Toxicology Centre, University of Saskatchewan, 44 Campus Drive, Saskatoon, SK, S7N 5B3, Canada; Institute for Environmental Research, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany. Electronic address: markus.brinkmann@usask.ca.
2
School of Environment & Sustainability and Toxicology Centre, University of Saskatchewan, 44 Campus Drive, Saskatoon, SK, S7N 5B3, Canada.
3
Department of Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, 44 Campus Drive, SK S7N 5B3 Saskatoon, Canada; Department of Zoology and Center for Integrative Toxicology, Michigan State University, East Lansing, MI, USA; School of Biological Sciences, University of Hong Kong, Kowloon, Hong Kong, SAR, China.
4
Institute for Environmental Research, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany.
5
Institute for Environmental Research, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany; College of Resources and Environmental Science, Chongqing University, 1 Tiansheng Road Beibei, Chongqing 400715, China; College of Environmental Science and Engineering, Tongji University, 1239 Siping Road, Shanghai, China; State Key Laboratory of Pollution Control and Resource Reuse, Tongji University, 1239 Siping Road, Shanghai, China; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, China.

Abstract

Cell-based bioanalytical tools are considered one alternative to overcome limitations of sensitivities of instrumental, analytical chemistry for monitoring estrogenic chemicals in the environment. Because these tools also reflect non-additive interactions of chemicals in mixtures, their outcomes often deviate from outcomes of chemical analytical approaches that assume additivity, e.g. the concentration addition (CA) model. Often this is because CA is unable to adequately represent effects of partial agonists, i.e. estrogens with lesser efficacies compared to 17β-estradiol. A generalized concentration addition (GCA) model has been proposed to address this shortcoming. In the present study, we investigated effects of mixtures of isomers of nonylphenol as partial model agonists in a cell-based estrogenicity assay. Whether the GCA model was able to more accurately predict the outcomes of these and previously published mixture experiments was evaluated, as well as the potency of a set of comprehensively characterized sewage effluent samples, compared to CA. If samples contained partial agonists, the GCA model consistently predicted potencies of mixtures and extracts of environmental samples more accurately than did the CA model. These findings enable more accurate estimations of potencies of estrogenicity explained by concentrations of agonists and partial agonists, thus significantly improving the ability to identify causative chemicals.

KEYWORDS:

Competitive antagonism; Concentration addition; EEF; EEQ; Estrogen receptor; Independent action

PMID:
29066353
DOI:
10.1016/j.tiv.2017.10.022
[Indexed for MEDLINE]

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