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Considerations and guidelines for mouse metabolic phenotyping in diabetes research

Overview of attention for article published in Diabetologia, November 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

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62 X users

Citations

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68 Dimensions

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164 Mendeley
Title
Considerations and guidelines for mouse metabolic phenotyping in diabetes research
Published in
Diabetologia, November 2017
DOI 10.1007/s00125-017-4495-9
Pubmed ID
Authors

Thierry Alquier, Vincent Poitout

Abstract

Mice are the most commonly used species in preclinical research on the pathophysiology of metabolic diseases. Although they are extremely useful for identifying pathways, mechanisms and genes regulating glucose and energy homeostasis, the specificities of the various mouse models and methodologies used to investigate a metabolic phenotype can have a profound impact on experimental results and their interpretation. This review aims to: (1) describe the most commonly used experimental tests to assess glucose and energy homeostasis in mice; (2) provide some guidelines regarding the design, analysis and interpretation of these tests, as well as for studies using genetic models; and (3) identify important caveats and confounding factors that must be taken into account in the interpretation of findings.

X Demographics

X Demographics

The data shown below were collected from the profiles of 62 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 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 164 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 21%
Student > Ph. D. Student 25 15%
Student > Master 22 13%
Student > Bachelor 13 8%
Student > Doctoral Student 8 5%
Other 24 15%
Unknown 38 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 56 34%
Agricultural and Biological Sciences 21 13%
Medicine and Dentistry 11 7%
Neuroscience 9 5%
Immunology and Microbiology 4 2%
Other 16 10%
Unknown 47 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 34. 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 06 November 2018.
All research outputs
#1,212,347
of 25,732,188 outputs
Outputs from Diabetologia
#642
of 5,376 outputs
Outputs of similar age
#22,920
of 319,765 outputs
Outputs of similar age from Diabetologia
#22
of 67 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,376 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.7. This one has done well, scoring higher than 88% 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 319,765 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 67 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 67% of its contemporaries.