| Title |
Effects of aging, exercise, and disease on force transfer in skeletal muscle
|
|---|---|
| Published in |
American Journal of Physiology: Endocrinology & Metabolism, May 2015
|
| DOI | 10.1152/ajpendo.00095.2015 |
| Pubmed ID | |
| Authors | |
| Abstract |
The loss of muscle strength and increased injury rate in aging skeletal muscle has previously been attributed to loss of muscle protein (cross-sectional area) and/or decreased neural activation. However, it is becoming clear that force transfer within and between fibers plays a significant role in this process as well. Force transfer involves a secondary matrix of proteins that align and transmit the force produced by the thick and thin filaments along muscle fibers and out to the extracellular matrix. These specialized networks of cytoskeletal proteins aid in passing force through the muscle and also serve to protect individual fibers from injury. This review will discuss the cytoskeleton proteins that have been identified as playing a role in muscle force transmission, both longitudinally and laterally, and where possible highlight how disease, aging and exercise influence the expression and function of these proteins. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 41 | 17% |
| United Kingdom | 40 | 16% |
| Spain | 18 | 7% |
| Australia | 8 | 3% |
| Canada | 8 | 3% |
| Brazil | 4 | 2% |
| Ireland | 4 | 2% |
| Chile | 4 | 2% |
| India | 3 | 1% |
| Other | 33 | 14% |
| Unknown | 81 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 162 | 66% |
| Scientists | 58 | 24% |
| Practitioners (doctors, other healthcare professionals) | 21 | 9% |
| Science communicators (journalists, bloggers, editors) | 2 | <1% |
| Unknown | 1 | <1% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | <1% |
| United States | 1 | <1% |
| Turkey | 1 | <1% |
| Netherlands | 1 | <1% |
| Finland | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 255 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 46 | 18% |
| Student > Bachelor | 41 | 16% |
| Student > Master | 33 | 13% |
| Researcher | 32 | 12% |
| Student > Doctoral Student | 15 | 6% |
| Other | 47 | 18% |
| Unknown | 48 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
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| Biochemistry, Genetics and Molecular Biology | 32 | 12% |
| Medicine and Dentistry | 29 | 11% |
| Agricultural and Biological Sciences | 28 | 11% |
| Nursing and Health Professions | 13 | 5% |
| Other | 29 | 11% |
| Unknown | 54 | 21% |