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Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA

Overview of attention for article published in Environmental Pollution, February 2017
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  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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5 tweeters
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1 Facebook page

Citations

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8 Dimensions

Readers on

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48 Mendeley
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Title
Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA
Published in
Environmental Pollution, February 2017
DOI 10.1016/j.envpol.2016.12.005
Pubmed ID
Authors

Anthony L. Schroeder, Dalma Martinović-Weigelt, Gerald T. Ankley, Kathy E. Lee, Natalia Garcia-Reyero, Edward J. Perkins, Heiko L. Schoenfuss, Daniel L. Villeneuve

Abstract

Evaluating potential adverse effects of complex chemical mixtures in the environment is challenging. One way to address that challenge is through more integrated analysis of chemical monitoring and biological effects data. In the present study, water samples from five locations near two municipal wastewater treatment plants in the St. Croix River basin, on the border of MN and WI, USA, were analyzed for 127 organic contaminants. Known chemical-gene interactions were used to develop site-specific knowledge assembly models (KAMs) and formulate hypotheses concerning possible biological effects associated with chemicals detected in water samples from each location. Additionally, hepatic gene expression data were collected for fathead minnows (Pimephales promelas) exposed in situ, for 12 d, at each location. Expression data from oligonucleotide microarrays were analyzed to identify functional annotation terms enriched among the differentially-expressed probes. The general nature of many of the terms made hypothesis formulation on the basis of the transcriptome-level response alone difficult. However, integrated analysis of the transcriptome data in the context of the site-specific KAMs allowed for evaluation of the likelihood of specific chemicals contributing to observed biological responses. Thirteen chemicals (atrazine, carbamazepine, metformin, thiabendazole, diazepam, cholesterol, p-cresol, phenytoin, omeprazole, ethyromycin, 17β-estradiol, cimetidine, and estrone), for which there was statistically significant concordance between occurrence at a site and expected biological response as represented in the KAM, were identified. While not definitive, the approach provides a line of evidence for evaluating potential cause-effect relationships between components of a complex mixture of contaminants and biological effects data, which can inform subsequent monitoring and investigation.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Brazil 1 2%
Unknown 46 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 38%
Researcher 9 19%
Other 6 13%
Student > Master 5 10%
Student > Postgraduate 3 6%
Other 3 6%
Unknown 4 8%
Readers by discipline Count As %
Environmental Science 12 25%
Chemistry 4 8%
Engineering 4 8%
Agricultural and Biological Sciences 3 6%
Biochemistry, Genetics and Molecular Biology 3 6%
Other 7 15%
Unknown 15 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 February 2017.
All research outputs
#3,240,475
of 12,279,872 outputs
Outputs from Environmental Pollution
#850
of 3,929 outputs
Outputs of similar age
#104,298
of 337,474 outputs
Outputs of similar age from Environmental Pollution
#54
of 224 outputs
Altmetric has tracked 12,279,872 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 3,929 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done well, scoring higher than 78% of its peers.
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 337,474 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 224 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.