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Intramyocellular lipid kinetics and insulin resistance

Overview of attention for article published in Lipids in Health and Disease, July 2007
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)

Mentioned by

blogs
1 blog
twitter
1 X user
wikipedia
1 Wikipedia page
video
2 YouTube creators

Citations

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22 Dimensions

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67 Mendeley
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Title
Intramyocellular lipid kinetics and insulin resistance
Published in
Lipids in Health and Disease, July 2007
DOI 10.1186/1476-511x-6-18
Pubmed ID
Authors

ZengKui Guo

Abstract

More than fifteen years ago it was discovered that intramyocellular triglyceride (imcTG) content in skeletal muscle is abnormally high in conditions of lipid oversupply (e.g. high fat feeding) and, later, obesity, type 2 diabetes (T2D) and other metabolic conditions. This imcTG excess is robustly associated with muscle insulin resistance (MIR). However, to date the pathways responsible for the imcTG excess and the mechanisms underlying the imcTG-MIR correlation remain unclear. A current hypothesis is based on a backward mechanism that impaired fatty acid oxidation by skeletal muscle causes imcTG to accumulate. As such, imcTG excess is considered a marker but not a player in MIR. However, recent results from kinetic studies indicated that imcTG pool in high fat-induced obesity (HFO) model is kinetically dynamic. On one hand, imcTG synthesis is accelerated and contributes to imcTG accumulation. On the other, the turnover of imcTG is also accelerated. A hyperdynamic imcTG pool can impose dual adverse effects on glucose metabolism in skeletal muscle. It increases the release and thus the availability of fatty acids in myocytes that may promote fatty acid oxidation and suppress glucose utilization. Meanwhile, it releases abundant fatty acid products (e.g. diacylglycerol, ceramides) that impair insulin actions via signal transduction, thereby causing MIR. Thus, intramyocellular fatty acids and their products released from imcTG appear to function as a link to MIR. Accordingly, a forward mechanism is proposed that explains the imcTG-MIR correlation.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Germany 1 1%
Switzerland 1 1%
Unknown 64 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 18%
Student > Bachelor 11 16%
Student > Ph. D. Student 10 15%
Student > Master 10 15%
Student > Doctoral Student 4 6%
Other 13 19%
Unknown 7 10%
Readers by discipline Count As %
Medicine and Dentistry 16 24%
Agricultural and Biological Sciences 16 24%
Biochemistry, Genetics and Molecular Biology 7 10%
Sports and Recreations 5 7%
Nursing and Health Professions 4 6%
Other 9 13%
Unknown 10 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 03 August 2023.
All research outputs
#2,267,592
of 25,374,917 outputs
Outputs from Lipids in Health and Disease
#167
of 1,607 outputs
Outputs of similar age
#4,705
of 76,295 outputs
Outputs of similar age from Lipids in Health and Disease
#1
of 3 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,607 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one has done well, scoring higher than 89% 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 76,295 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 93% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them