Denervation-induced mitochondrial dysfunction and autophagy in skeletal muscle of apoptosis-deficient animals
Bibliographic record
Abstract
Skeletal muscle undergoes remarkable adaptations in response to chronic decreases in contractile activity, such as a loss of muscle mass, decreases in both mitochondrial content and function, as well as the activation of apoptosis. Although these adaptations are well known, questions remain regarding the signaling pathways that mediated these changes. Autophagy is an organelle turnover pathway that could contribute to these adaptations. The purpose of this study was to determine whether denervation-induced muscle disuse would result in the activation of autophagy gene expression in both wild-type (WT) and Bax/Bak double knockout (DKO) animals, which display an attenuated apoptotic response. Denervation caused a reduction in muscle mass for WT and DKO animals; however, there was a 40% attenuation in muscle atrophy in DKO animals. Mitochondrial state 3 respiration was significantly reduced, and reactive oxygen species production was increased by two- to threefold in both WT and DKO animals. Apoptotic markers, including cytosolic AIF and DNA fragmentation, were elevated in WT, but not in DKO animals following denervation. Autophagy proteins including LC3II, ULK1, ATG7, p62, and Beclin1 were increased similarly following denervation for both WT and DKO. Interestingly, denervation markedly increased the localization of LC3II to subsarcolemmal mitochondria, and this was more pronounced in the DKO animals. Thus denervation-induced muscle disuse activates both apoptotic and autophagic signaling pathways in muscle, and autophagic protein expression does not exhibit a compensatory increase in the presence of attenuated apoptosis. However, the absence of Bax and Bak may represent a potential signal to trigger mitophagy in 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".