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X Demographics
Mendeley readers
Attention Score in Context
| Title |
TAK-1/p38/nNFκB signaling inhibits myoblast differentiation by increasing levels of Activin A
|
|---|---|
| Published in |
Skeletal Muscle, February 2012
|
| DOI | 10.1186/2044-5040-2-3 |
| Pubmed ID | |
| Authors |
Anne Ulrike Trendelenburg, Angelika Meyer, Carsten Jacobi, Jerome N Feige, David J Glass |
| Abstract |
Skeletal-muscle differentiation is required for the regeneration of myofibers after injury. The differentiation capacity of satellite cells is impaired in settings of old age, which is at least one factor in the onset of sarcopenia, the age-related loss of skeletal-muscle mass and major cause of frailty. One important cause of impaired regeneration is increased levels of transforming growth factor (TGF)-β accompanied by reduced Notch signaling. Pro-inflammatory cytokines are also upregulated in aging, which led us hypothesize that they might potentially contribute to impaired regeneration in sarcopenia. Thus, in this study, we further analyzed the muscle differentiation-inhibition pathway mediated by pro-inflammatory cytokines in human skeletal muscle cells (HuSKMCs). |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Norway | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 100 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 23% |
| Researcher | 20 | 20% |
| Student > Master | 8 | 8% |
| Student > Bachelor | 5 | 5% |
| Professor > Associate Professor | 5 | 5% |
| Other | 12 | 12% |
| Unknown | 29 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 23 | 23% |
| Biochemistry, Genetics and Molecular Biology | 18 | 18% |
| Medicine and Dentistry | 14 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 6% |
| Immunology and Microbiology | 3 | 3% |
| Other | 6 | 6% |
| Unknown | 32 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 16 February 2012.
All research outputs
#2,562,418
of 25,374,917 outputs
Outputs from Skeletal Muscle
#50
of 388 outputs
Outputs of similar age
#19,220
of 253,979 outputs
Outputs of similar age from Skeletal Muscle
#1
of 5 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 388 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done well, scoring higher than 87% 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 253,979 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 5 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