Skeletal muscle apoptotic response to physical activity: potential mechanisms for protection
Bibliographic record
Abstract
Apoptosis is a highly conserved type of cell death that plays a critical role in tissue homeostasis and disease-associated processes. Skeletal muscle is unique with respect to apoptotic processes, given its multinucleated morphology and its apoptosis-associated differences related to muscle and (or) fiber type as well as mitochondrial content and (or) subtype. Elevated apoptotic signaling has been reported in skeletal muscle during aging, stress-induced states, and disease; a phenomenon that plays a role in muscle dysfunction, degradation, and atrophy. Exercise is a strong physiological stimulus that can influence a number of extracellular and intracellular signaling pathways, which may directly or indirectly influence apoptotic processes in skeletal muscle. In general, acute strenuous and eccentric exercise are associated with a proapoptotic phenotype and increased DNA fragmentation (a hallmark of apoptosis), whereas regular exercise training or activity is associated with an antiapoptotic environment and reduced DNA fragmentation in skeletal muscle. Interestingly, the protective effect of regular activity on skeletal muscle apoptotic processes has been observed in healthy, aged, stress-induced, and diseased rodent models. Several mechanisms for this protective response have been proposed, including altered anti- and proapoptotic protein expression, increased mitochondrial biogenesis and improved mitochondrial function, and reduced reactive oxygen species generation and (or) enhanced antioxidant status. Given the current literature, we propose that regular physical activity may represent an effective strategy to decrease apoptotic signaling, and possibly muscle wasting and dysfunction, during aging and disease.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".