Exercise and mitochondrial health
Bibliographic record
Abstract
Mitochondrial health is an important mediator of cellular function across a range of tissues, and as a result contributes to whole-body vitality in health and disease. Our understanding of the regulation and function of these organelles is of great interest to scientists and clinicians across many disciplines within our healthcare system. Skeletal muscle is a useful model tissue for the study of mitochondrial adaptations because of its mass and contribution to whole body metabolism. The remarkable plasticity of mitochondria allows them to adjust their volume, structure and capacity under conditions such as exercise, which is useful or improving metabolic health in individuals with various diseases and/or advancing age. Mitochondria exist within muscle as a functional reticulum which is maintained by dynamic processes of biogenesis and fusion, and is balanced by opposing processes of fission and mitophagy. The sophisticated coordination of these events is incompletely understood, but is imperative for organelle function and essential for the maintenance of an interconnected organelle network that is finely tuned to the metabolic needs of the cell. Further elucidation of the mechanisms of mitochondrial turnover in muscle could offer potential therapeutic targets for the advancement of health and longevity among our ageing populations. As well, investigating exercise modalities that are both convenient and capable of inducing robust mitochondrial adaptations are useful in fostering more widespread global adherence. To this point, exercise remains the most potent behavioural therapeutic approach for the improvement of mitochondrial health, not only in muscle, but potentially also in other tissues.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".