Mechanisms of mechanical overload-induced skeletal muscle hypertrophy: current understanding and future directions
Bibliographic record
Abstract
Mechanisms underlying mechanical overload-induced skeletal muscle hypertrophy have been extensively researched since the landmark report by Morpurgo (1897) of "work-induced hypertrophy" in dogs that were treadmill trained. Much of the preclinical rodent and human resistance training research to date supports that involved mechanisms include enhanced mammalian/mechanistic target of rapamycin complex 1 (mTORC1) signaling, an expansion in translational capacity through ribosome biogenesis, increased satellite cell abundance and myonuclear accretion, and postexercise elevations in muscle protein synthesis rates. However, several lines of past and emerging evidence suggest that additional mechanisms that feed into or are independent of these processes are also involved. This review first provides a historical account of how mechanistic research into skeletal muscle hypertrophy has progressed. A comprehensive list of mechanisms associated with skeletal muscle hypertrophy is then outlined, and areas of disagreement involving these mechanisms are presented. Finally, future research directions involving many of the discussed mechanisms are proposed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".