Regulation of the autophagy system during chronic contractile activity-induced muscle adaptations
Bibliographic record
Abstract
Skeletal muscle is adaptable to exercise stimuli via the upregulation of mitochondrial biogenesis, and recent studies have suggested that autophagy also plays a role in exercise-induced muscle adaptations. However, it is still obscure how muscle regulates autophagy over the time course of training adaptations. This study examined the expression of autophagic proteins in skeletal muscle of rats exposed to chronic contractile activity (CCA; 6 h/day, 9V, 10 Hz continuous, 0.1 msec pulse duration) for 1, 3, and 7 days (n = 8/group). CCA-induced mitochondrial adaptations were observed by day 7, as shown by the increase in mitochondrial proteins (PGC-1α, COX I, and COX IV), as well as COX activity. Notably, the ratio of LC3 II/LC3 I, an indicator of autophagy, decreased by day 7 largely due to a significant increase in LC3 I. The autophagic induction marker p62 was elevated on day 3 and returned to basal levels by day 7, suggesting a time-dependent increase in autophagic flux. The lysosomal system was upregulated early, prior to changes in mitochondrial proteins, as represented by increases in lysosomal system markers LAMP1, LAMP2A, and MCOLN1 as early as by day 1, as well as TFEB, a primary regulator of lysosomal biogenesis and autophagy flux. Our findings suggest that, in response to chronic exercise, autophagy is upregulated concomitant with mitochondrial adaptations. Notably, our data reveal the surprising adaptive plasticity of the lysosome in response to chronic contractile activity which enhances muscle health by providing cells with a greater capacity for macromolecular and organelle turnover.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".