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• W2326486586 abstract "Abstract The ability to focus on the most biologically relevant contaminants affecting aquatic ecosystems can be challenging because toxicity‐assessment programs have not kept pace with the growing number of contaminants requiring testing. Because it has proven effective at assessing the biological impacts of potentially toxic contaminants, profiling of endogenous metabolites (metabolomics) may help screen out contaminants with a lower likelihood of eliciting biological impacts, thereby prioritizing the most biologically important contaminants. The authors present results from a study that utilized cage‐deployed fathead minnows ( Pimephales promelas ) at 18 sites across the Great Lakes basin. They measured water temperature and contaminant concentrations in water samples (132 contaminants targeted, 86 detected) and used 1 H‐nuclear magnetic resonance spectroscopy to measure endogenous metabolites in polar extracts of livers. They used partial least‐squares regression to compare relative abundances of endogenous metabolites with contaminant concentrations and temperature. The results indicated that profiles of endogenous polar metabolites covaried with at most 49 contaminants. The authors identified up to 52% of detected contaminants as not significantly covarying with changes in endogenous metabolites, suggesting they likely were not eliciting measurable impacts at these sites. This represents a first step in screening for the biological relevance of detected contaminants by shortening lists of contaminants potentially affecting these sites. Such information may allow risk assessors to prioritize contaminants and focus toxicity testing on the most biologically relevant contaminants. Environ Toxicol Chem 2016;35:2493–2502. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US Government work and, as such, is in the public domain in the United States of America." @default.
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• W2326486586 date "2016-06-21" @default.
• W2326486586 modified "2023-10-18" @default.
• W2326486586 title "Linking field‐based metabolomics and chemical analyses to prioritize contaminants of emerging concern in the Great Lakes basin" @default.
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• W2326486586 doi "https://doi.org/10.1002/etc.3409" @default.
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