Mechano‐biology of skeletal muscle hypertrophy and regeneration: Possible mechanism of stretch‐induced activation of resident myogenic stem cells
Why this work is in the frame
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Bibliographic record
Abstract
In undamaged postnatal muscle fibers with normal contraction and relaxation activities, quiescent satellite cells of resident myogenic stem cells are interposed between the overlying external lamina and the sarcolemma of a subjacent mature muscle fiber. When muscle is injured, exercised, overused or mechanically stretched, these cells are activated to enter the cell proliferation cycle, divide, differentiate, and fuse with the adjacent muscle fiber, and are responsible for regeneration and work-induced hypertrophy of muscle fibers. Therefore, a mechanism must exist to translate mechanical changes in muscle tissue into chemical signals that can activate satellite cells. Recent studies of satellite cells or single muscle fibers in culture and in vivo demonstrated the essential role of hepatocyte growth factor (HGF) and nitric oxide (NO) radical in the activation pathway. These experiments have also reported that mechanically stretching satellite cells or living skeletal muscles triggers the activation by rapid release of HGF from its extracellular tethering and the subsequent presentation to the receptor c-met. HGF release has been shown to rely on calcium-calmodulin formation and NO radical production in satellite cells and/or muscle fibers in response to the mechanical perturbation, and depend on the subsequent up-regulation of matrix metalloproteinase (MMP) activity. These results indicate that the activation mechanism is a cascade of events including calcium ion influx, calcium-calmodulin formation, NO synthase activation, NO radical production, MMP activation, HGF release and binding to c-met. Better understanding of 'mechano-biology' on the satellite cell activation is essential for designing procedures that could enhance muscle growth and repair activities in meat-animal agriculture and also in neuromuscular disease and aging in humans.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it