Mitochondrial Bioenergetics and Turnover during Chronic Muscle Disuse
Bibliographic record
Abstract
Periods of muscle disuse promote marked mitochondrial alterations that contribute to the impaired metabolic health and degree of atrophy in the muscle. Thus, understanding the molecular underpinnings of muscle mitochondrial decline with prolonged inactivity is of considerable interest. There are translational applications to patients subjected to limb immobilization following injury, illness-induced bed rest, neuropathies, and even microgravity. Studies in these patients, as well as on various pre-clinical rodent models have elucidated the pathways involved in mitochondrial quality control, such as mitochondrial biogenesis, mitophagy, fission and fusion, and the corresponding mitochondrial derangements that underlie the muscle atrophy that ensues from inactivity. Defective organelles display altered respiratory function concurrent with increased accumulation of reactive oxygen species, which exacerbate myofiber atrophy via degradative pathways. The preservation of muscle quality and function is critical for maintaining mobility throughout the lifespan, and for the prevention of inactivity-related diseases. Exercise training is effective in preserving muscle mass by promoting favourable mitochondrial adaptations that offset the mitochondrial dysfunction, which contributes to the declines in muscle and whole-body metabolic health. This highlights the need for further investigation of the mechanisms in which mitochondria contribute to disuse-induced atrophy, as well as the specific molecular targets that can be exploited therapeutically.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".