Mechanisms of Exercise‐Induced Mitochondrial Biogenesis in Skeletal Muscle: Implications for Health and Disease
Bibliographic record
Abstract
Mitochondria have paradoxical functions within cells. Essential providers of energy for cellular survival, they are also harbingers of cell death (apoptosis). Mitochondria exhibit remarkable dynamics, undergoing fission, fusion, and reticular expansion. Both nuclear and mitochondrial DNA (mtDNA) encode vital sets of proteins which, when incorporated into the inner mitochondrial membrane, provide electron transport capacity for ATP production, and when mutated lead to a broad spectrum of diseases. Acute exercise can activate a set of signaling cascades in skeletal muscle, leading to the activation of the gene expression pathway, from transcription, to post-translational modifications. Research has begun to unravel the important signals and their protein targets that trigger the onset of mitochondrial adaptations to exercise. Exercise training leads to an accumulation of nuclear- and mtDNA-encoded proteins that assemble into functional complexes devoted to mitochondrial respiration, reactive oxygen species (ROS) production, the import of proteins and metabolites, or apoptosis. This process of biogenesis has important consequences for metabolic health, the oxidative capacity of muscle, and whole body fitness. In contrast, the chronic muscle disuse that accompanies aging or muscle wasting diseases provokes a decline in mitochondrial content and function, which elicits excessive ROS formation and apoptotic signaling. Research continues to seek the molecular underpinnings of how regular exercise can be used to attenuate these decrements in organelle function, maintain skeletal muscle health, and improve quality of life.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.004 | 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".