Inhibition of the Fission Machinery Mitigates OPA1 Impairment in Adult Skeletal Muscles
Bibliographic record
Abstract
The maintenance of muscle mass and its ability to function relies on a bioenergetic efficient mitochondrial network. This network is highly impacted by fusion and fission events. We have recently shown that the acute deletion of the fusion protein Opa1 induces muscle atrophy, systemic inflammatory response, precocious epithelial senescence, and premature death that are caused by muscle-dependent secretion of FGF21. However, both fusion and fission machinery are suppressed in aging sarcopenia, cancer cachexia, and chemotherapy-induced muscle wasting. We generated inducible muscle-specific Opa1 and Drp1 double-knockout mice to address the physiological relevance of the concomitant impairment of fusion and fission machinery in skeletal muscle. Here we show that acute ablation of Opa1 and Drp1 in adult muscle causes the accumulation of abnormal and dysfunctional mitochondria, as well as the inhibition of autophagy and mitophagy pathways. This ultimately results in ER stress, muscle loss, and the reduction of force generation. However, the simultaneous inhibition of the fission protein Drp1 when Opa1 is absent alleviates FGF21 induction, oxidative stress, denervation, and inflammation rescuing the lethal phenotype of Opa1 knockout mice, despite the presence of any muscle weakness. Thus, the simultaneous inhibition of fusion and fission processes mitigates the detrimental effects of unbalanced mitochondrial fusion and prevents the secretion of pro-senescence factors.
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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 | 0.000 | 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) | 0.001 | 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".