Perspectives on the interpretation of mitochondrial responses during skeletal muscle disuse‐induced atrophy
Bibliographic record
Abstract
Reductions in skeletal muscle mitochondrial respiration or increases in mitochondrial reactive oxygen species (ROS) are often interpreted as 'mitochondrial dysfunctions'. However, such changes can also occur as intentional programmed responses to stressors. The term 'mitochondrial dysfunction' could therefore consider the net impact of such responses on other cellular functions. In the case of disuse-induced skeletal muscle atrophy, lower mitochondrial respiration, increased ROS and increased mitochondrial-linked apoptosis have been associated with muscle loss. Such observations support hypotheses that mitochondria contribute to atrophy. If true, there are exciting opportunities for exploring therapeutic strategies that prevent such changes in mitochondrial metabolism. These observations might also support alternative hypotheses where mitochondria are intentionally reprogrammed to serve specific purposes, such as a recalibration of ATP supply to reduced ATP demand during disuse. The goal of this review is to describe what is known regarding skeletal muscle mitochondrial functional responses to muscle disuse, as well as to discuss how these foundational discoveries might lead to new directions that determine whether mitochondrial responses to disuse are causal of atrophy or are adaptive in nature. Three critical questions for consideration include: (1) when is a change in mitochondrial function 'dysfunctional'; (2) how might changes in mitochondrial function represent intentional reprogramming to serve specific purposes; and (3) what factors should be considered when constructing experimental designs to determine the role of mitochondrial functional responses to disuse? Understanding when mitochondrial functional remodelling are dysfunctions or adaptive responses could inform new therapeutic approaches to maintain muscle mass during periods of disuse.
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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 | 0.011 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".