| Title |
Skeletal muscle in aged mice reveals extensive transformation of muscle gene expression
|
|---|---|
| Published in |
BMC Genomic Data, August 2018
|
| DOI | 10.1186/s12863-018-0660-5 |
| Pubmed ID | |
| Authors |
I-Hsuan Lin, Junn-Liang Chang, Kate Hua, Wan-Chen Huang, Ming-Ta Hsu, Yi-Fan Chen |
| Abstract |
Aging leads to decreased skeletal muscle function in mammals and is associated with a progressive loss of muscle mass, quality and strength. Age-related muscle loss (sarcopenia) is an important health problem associated with the aged population. We investigated the alteration of genome-wide transcription in mouse skeletal muscle tissue (rectus femoris muscle) during aging using a high-throughput sequencing technique. Analysis revealed significant transcriptional changes between skeletal muscles of mice at 3 (young group) and 24 (old group) months of age. Specifically, genes associated with energy metabolism, cell proliferation, muscle myosin isoforms, as well as immune functions were found to be altered. We observed several interesting gene expression changes in the elderly, many of which have not been reported before. Those data expand our understanding of the various compensatory mechanisms that can occur with age, and further will assist in the development of methods to prevent and attenuate adverse outcomes of aging. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 109 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 24% |
| Student > Bachelor | 13 | 12% |
| Researcher | 12 | 11% |
| Student > Doctoral Student | 10 | 9% |
| Student > Master | 9 | 8% |
| Other | 11 | 10% |
| Unknown | 28 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 28 | 26% |
| Agricultural and Biological Sciences | 19 | 17% |
| Medicine and Dentistry | 8 | 7% |
| Engineering | 4 | 4% |
| Nursing and Health Professions | 4 | 4% |
| Other | 15 | 14% |
| Unknown | 31 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 10 August 2018.
All research outputs
#17,292,294
of 25,385,509 outputs
Outputs from BMC Genomic Data
#667
of 1,204 outputs
Outputs of similar age
#219,755
of 341,021 outputs
Outputs of similar age from BMC Genomic Data
#16
of 31 outputs
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