Disuse-induced skeletal muscle atrophy in disease and nondisease states in humans: mechanisms, prevention, and recovery strategies
Bibliographic record
Abstract
Decreased skeletal muscle contractile activity (disuse) or unloading leads to muscle mass loss, also known as muscle atrophy. The balance between muscle protein synthesis (MPS) and muscle protein breakdown (MPB) is the primary determinant of skeletal muscle mass. A reduced mechanical load on skeletal muscle is one of the main external factors leading to muscle atrophy. However, endocrine and inflammatory factors can act synergistically in catabolic states, amplifying the atrophy process and accelerating its progression. In addition, older individuals display aging-induced anabolic resistance, which can predispose this population to more pronounced effects when exposed to periods of reduced physical activity or mechanical unloading. Different cellular mechanisms contribute to the regulation of muscle protein balance during skeletal muscle atrophy. This review summarizes the effects of muscle disuse on muscle protein balance and the molecular mechanisms involved in muscle atrophy in the absence or presence of disease. Finally, a discussion of the current literature describing efficient strategies to prevent or improve the recovery from muscle atrophy is also presented.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".