Autophagy is not required to sustain exercise and PRKAA1/AMPK activity but is important to prevent mitochondrial damage during physical activity
Bibliographic record
Abstract
Physical activity has been recently documented to play a fundamental physiological role in the regulation of autophagy in several tissues. It has also been reported that autophagy is required for exercise itself and for training-induced adaptations in glucose homeostasis. These autophagy-mediated metabolic improvements are thought to be largely dependent on the activation of the metabolic sensor PRKAA1/AMPK. However, it is unknown whether these important benefits stem from systemic adaptations or are due solely to alterations in skeletal muscle metabolism. To address this we utilized inducible, muscle-specific, atg7 knockout mice that we have recently generated. Our findings indicate that acute inhibition of autophagy in skeletal muscle just prior to exercise does not have an impact on physical performance, PRKAA1 activation, or glucose homeostasis. However, we reveal that autophagy is critical for the preservation of mitochondrial function during damaging muscle contraction. This effect appears to be gender specific affecting primarily females. We also establish that basal oxidative stress plays a crucial role in mitochondrial maintenance during normal physical activity. Therefore, autophagy is an adaptive response to exercise that ensures effective mitochondrial quality control during damaging physical activity.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".