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Linking field‐based metabolomics and chemical analyses to prioritize contaminants of emerging concern in the Great Lakes basin

Overview of attention for article published in Environmental Toxicology & Chemistry, June 2016
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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Title
Linking field‐based metabolomics and chemical analyses to prioritize contaminants of emerging concern in the Great Lakes basin
Published in
Environmental Toxicology & Chemistry, June 2016
DOI 10.1002/etc.3409
Pubmed ID
Authors

John M. Davis, Drew R. Ekman, Quincy Teng, Gerald T. Ankley, Jason P. Berninger, Jenna E. Cavallin, Kathleen M. Jensen, Michael D. Kahl, Anthony L. Schroeder, Daniel L. Villeneuve, Zachary G. Jorgenson, Kathy E. Lee, Timothy W. Collette

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 in assessing 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. We present results from a study that utilized cage-deployed fathead minnows (Pimephales promelas) at 18 sites across the Great Lakes basin. We measured water temperature and contaminant concentrations in water samples (132 contaminants targeted; 86 detected), and used (1) H-NMR spectroscopy to measure endogenous metabolites in polar extracts of livers. We used partial least-squares (PLS) regression to compare relative abundances of endogenous metabolites with contaminant concentrations and temperature. Results indicated that profiles of endogenous polar metabolites covaried with at most 49 contaminants. Thus, we identified up to 52% of detected contaminants as not significantly covarying with changes in endogenous metabolites, suggesting they likely were not eliciting measureable 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. This article is protected by copyright. All rights reserved.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 18%
Researcher 9 16%
Student > Ph. D. Student 6 11%
Professor 3 5%
Other 3 5%
Other 8 14%
Unknown 17 30%
Readers by discipline Count As %
Environmental Science 15 27%
Agricultural and Biological Sciences 5 9%
Biochemistry, Genetics and Molecular Biology 4 7%
Chemistry 3 5%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 6 11%
Unknown 21 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 April 2016.
All research outputs
#16,048,009
of 25,374,917 outputs
Outputs from Environmental Toxicology & Chemistry
#3,875
of 5,612 outputs
Outputs of similar age
#216,581
of 369,267 outputs
Outputs of similar age from Environmental Toxicology & Chemistry
#64
of 163 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,612 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 369,267 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 163 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.