Adaptive plasticity of autophagic proteins to denervation in aging skeletal muscle
Bibliographic record
Abstract
Aging muscle exhibits a progressive decline in mass and strength, known as sarcopenia, and a decrease in the adaptive response to contractile activity. The molecular mechanisms mediating this reduced plasticity have yet to be elucidated. The purposes of this study were 1) to determine whether denervation-induced muscle disuse would increase the expression of autophagy genes and 2) to examine whether selective autophagy pathways (mitophagy) are altered in aged animals. Denervation reduced muscle mass in young and aged animals by 24 and 16%, respectively. Moreover, young animals showed a 50% decrease in mitochondrial content following denervation, an adaptation that was not matched by aged animals. Basal autophagy protein expression was higher in aged animals, whereas young animals exhibited a greater induction of autophagy proteins following denervation. Localization of LC3II, Parkin, and p62 was significantly increased in the mitochondrial fraction of young and aged animals following denervation. Moreover, the unfolded protein response marker CHOP and the mitochondrial dynamics protein Fis1 were increased by 17- and 2.5-fold, respectively, in aged animals. Lipofuscin granules within lysosomes were evident with aging and denervation. Thus reductions in the adaptive plasticity of aged muscle are associated with decreases in disuse-induced autophagy. These data indicate that the expression of autophagy proteins and their localization to mitochondria are not decreased in aged muscle; however, the induction of autophagy in response to disuse, along with downstream events such as lysosome function, is impaired. This may contribute to an accumulation of dysfunctional mitochondria in aged muscle.
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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) | 0.000 | 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".