Article ID Journal Published Year Pages File Type
4530106 Aquatic Toxicology 2011 10 Pages PDF
Abstract

The presence of highly complex mixtures of chemicals in the environment challenges our ability to assess single chemical effects and the interaction that occurs with cellular receptor targets and regulation of endocrine processes. In this study concentration addition (CA) and independent action (IA) prediction models were used to assess the combined toxicity of mixtures of environmental relevant estrogen receptor (ER) agonists (hormones and anthropogenic pollutants) in a primary culture of rainbow trout (Oncorhynchus mykiss) hepatocytes using the ER-mediated production of vitellogenin (Vtg) as a biological marker (biomarker) for estrogenicity. Nine of the eleven tested chemicals induced the production of Vtg and the parameters from the fitted concentration–response curves were used to model four mixtures containing four (17β-estradiol, estrone, estriol and diethylstilbestrol), five (musk ketone, 4-tert-octylphenol, bisphenol A, o,p′-DDT and dibenzothiophene), seven (17β-estradiol, estrone, estriol, diethylstilbestrol, 4-tert-octylphenol, bisphenol A and o,p′-DDT) and nine compounds (17β-estradiol, estrone, estriol, diethylstilbestrol, musk ketone, 4-tert-octylphenol, bisphenol A, o,p′-DDT and dibenzothiophene). The CA and IA prediction model proved to be a good estimation for the combined effect of mixtures of ER agonists at low relative mixture concentration (e.g. relative to the maximum mixture concentrations used), but a deviation from the prediction models was observed when exposing hepatocytes to high relative mixture concentrations. The CA and IA prediction models’ ability to predict the combined estrogenic effect of complex mixtures, especially in the low concentration–response range, is of ecological relevance since organisms in the environment generally encounter low concentrations of chemicals from a wide array of chemical groups that may not elicit estrogenic effects on their own.

Related Topics
Life Sciences Agricultural and Biological Sciences Aquatic Science
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