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TOOLS TO MINIMIZE INTER‐LABORATORY VARIABILITY IN VITELLOGENIN GENE EXPRESSION MONITORING PROGRAMS

Overview of attention for article published in Environmental Toxicology & Chemistry, June 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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4 tweeters

Citations

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3 Dimensions

Readers on

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14 Mendeley
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Title
TOOLS TO MINIMIZE INTER‐LABORATORY VARIABILITY IN VITELLOGENIN GENE EXPRESSION MONITORING PROGRAMS
Published in
Environmental Toxicology & Chemistry, June 2017
DOI 10.1002/etc.3885
Pubmed ID
Authors

Jastrow, Aaron, Gordon, Denise A., Auger, Kasie M., Punska, Elizabeth C., Arcaro, Kathleen F., Keteles, Kristen, Winkelman, Dana, Lattier, David, Biales, Adam, Lazorchak, James M.

Abstract

The egg yolk precursor protein vitellogenin is widely used as a biomarker of estrogen exposure in male fish. However, standardized methodology is lacking and little is known regarding the reproducibility of results among laboratories using different equipment, reagents, protocols, and employing different data analysis programs. To address this data gap we tested the reproducibility across labs to evaluate vitellogenin gene (vtg) expression and assessed the value of using a freely available software data analysis program. Samples collected from studies of male fathead minnows (Pimephales promelas) exposed to 17α-ethinylestradiol (EE2) and minnows exposed to processed wastewater effluent were evaluated for vtg expression in four laboratories. Our results indicate reasonable consistency among laboratories if the free software for expression analysis, LinRegPCR, is used; with three out of four laboratories detecting vtg in fish exposed to 5 ng/L EE2 (n = 5). All four laboratories detected significantly increased vtg levels in 15 male fish exposed to wastewater effluent as compared to 15 male fish held in a control stream. Finally, we were able to determine that the source of high inter-laboratory variability from cDNA to qPCR analyses was the expression analysis software unique to each real-time quantitative polymerase chain reaction (qPCR) machine. We successfully eliminated the inter-laboratory variability by reanalyzing raw fluorescence data with independent freeware, which yielded cycle thresholds and PCR efficiencies that calculated results independently of proprietary software. Our results suggest that laboratories engaged in monitoring programs validate their PCR protocols and analyze their gene expression data following the guidelines established herein for all gene expression biomarkers. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 29%
Professor 2 14%
Other 2 14%
Student > Master 2 14%
Student > Ph. D. Student 2 14%
Other 2 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 29%
Biochemistry, Genetics and Molecular Biology 3 21%
Environmental Science 2 14%
Chemistry 1 7%
Unknown 4 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 29 October 2017.
All research outputs
#6,146,058
of 12,066,743 outputs
Outputs from Environmental Toxicology & Chemistry
#1,761
of 3,266 outputs
Outputs of similar age
#99,944
of 268,864 outputs
Outputs of similar age from Environmental Toxicology & Chemistry
#22
of 95 outputs
Altmetric has tracked 12,066,743 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,266 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 45th percentile – i.e., 45% 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 268,864 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 62% of its contemporaries.
We're also able to compare this research output to 95 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.