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A simple and rapid method to characterize lipid fate in skeletal muscle

Overview of attention for article published in BMC Research Notes, June 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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4 X users

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27 Mendeley
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Title
A simple and rapid method to characterize lipid fate in skeletal muscle
Published in
BMC Research Notes, June 2014
DOI 10.1186/1756-0500-7-391
Pubmed ID
Authors

Julie Massart, Juleen R Zierath, Alexander V Chibalin

Abstract

Elevated fatty acids contribute to the development of type 2 diabetes and affect skeletal muscle insulin sensitivity. Since elevated intramuscular lipids and insulin resistance is strongly correlated, aberrant lipid storage or lipid intermediates may be involved in diabetes pathogenesis. The aim of this study was to develop a method to determine the dynamic metabolic fate of lipids in primary human skeletal muscle cells and in intact mouse skeletal muscle. We report a simple and fast method to characterize lipid profiles in skeletal muscle using thin layer chromatography.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 22%
Student > Bachelor 6 22%
Researcher 3 11%
Other 2 7%
Student > Master 2 7%
Other 2 7%
Unknown 6 22%
Readers by discipline Count As %
Chemistry 5 19%
Agricultural and Biological Sciences 4 15%
Sports and Recreations 3 11%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Social Sciences 2 7%
Other 4 15%
Unknown 7 26%
Attention Score in Context

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 27 January 2017.
All research outputs
#13,195,543
of 22,792,160 outputs
Outputs from BMC Research Notes
#1,617
of 4,262 outputs
Outputs of similar age
#108,856
of 228,161 outputs
Outputs of similar age from BMC Research Notes
#42
of 96 outputs
Altmetric has tracked 22,792,160 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 61% 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 228,161 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 51% of its contemporaries.
We're also able to compare this research output to 96 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 56% of its contemporaries.