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Transcriptomic Effects-Based Monitoring for Endocrine Active Chemicals: Assessing Relative Contribution of Treated Wastewater to Downstream Pollution

Overview of attention for article published in Environmental Science & Technology, January 2014
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  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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3 tweeters

Citations

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38 Dimensions

Readers on

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69 Mendeley
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Title
Transcriptomic Effects-Based Monitoring for Endocrine Active Chemicals: Assessing Relative Contribution of Treated Wastewater to Downstream Pollution
Published in
Environmental Science & Technology, January 2014
DOI 10.1021/es404027n
Pubmed ID
Authors

Dalma Martinović-Weigelt, Alvine C. Mehinto, Gerald T. Ankley, Nancy D. Denslow, Larry B. Barber, Kathy E. Lee, Ryan J. King, Heiko L. Schoenfuss, Anthony L. Schroeder, Daniel L. Villeneuve

Abstract

The present study investigated whether a combination of targeted analytical chemistry information with unsupervised, data-rich biological methodology (i.e., transcriptomics) could be utilized to evaluate relative contributions of wastewater treatment plant (WWTP) effluents to biological effects. The effects of WWTP effluents on fish exposed to ambient, receiving waters were studied at three locations with distinct WWTP and watershed characteristics. At each location, 4 d exposures of male fathead minnows to the WWTP effluent and upstream and downstream ambient waters were conducted. Transcriptomic analyses were performed on livers using 15,000 feature microarrays, followed by a canonical pathway and gene set enrichment analyses. Enrichment of gene sets indicative of teleost brain-pituitary-gonadal-hepatic (BPGH) axis function indicated that WWTPs serve as an important source of endocrine active chemicals (EACs) that affect the BPGH axis (e.g., cholesterol and steroid metabolism were altered). The results indicated that transcriptomics may even pinpoint pertinent adverse outcomes (i.e., liver vacuolization) and groups of chemicals that preselected chemical analytes may miss. Transcriptomic Effects-Based monitoring was capable of distinguishing sites, and it reflected chemical pollution gradients, thus holding promise for assessment of relative contributions of point sources to pollution and the efficacy of pollution remediation.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Germany 1 1%
Unknown 66 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 26%
Researcher 16 23%
Student > Master 10 14%
Professor 6 9%
Other 4 6%
Other 7 10%
Unknown 8 12%
Readers by discipline Count As %
Environmental Science 22 32%
Agricultural and Biological Sciences 13 19%
Chemistry 5 7%
Biochemistry, Genetics and Molecular Biology 4 6%
Pharmacology, Toxicology and Pharmaceutical Science 3 4%
Other 8 12%
Unknown 14 20%

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 04 April 2014.
All research outputs
#1,784,041
of 4,507,509 outputs
Outputs from Environmental Science & Technology
#2,211
of 4,705 outputs
Outputs of similar age
#40,688
of 120,732 outputs
Outputs of similar age from Environmental Science & Technology
#115
of 251 outputs
Altmetric has tracked 4,507,509 research outputs across all sources so far. This one has received more attention than most of these and is in the 58th percentile.
So far Altmetric has tracked 4,705 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has gotten more attention than average, scoring higher than 50% 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 120,732 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 64% of its contemporaries.
We're also able to compare this research output to 251 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 50% of its contemporaries.