PGC-1α-mediated regulation of mitochondrial function and physiological implications
Bibliographic record
Abstract
The majority of human energy metabolism occurs in skeletal muscle mitochondria emphasizing the importance of understanding the regulation of myocellular mitochondrial function. The transcriptional co-activator peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α) has been characterized as a major factor in the transcriptional control of several mitochondrial components. Thus, PGC-1α is often described as a master regulator of mitochondrial biogenesis as well as a central player in regulating the antioxidant defense. However, accumulating evidence suggests that PGC-1α is also involved in the complex regulation of mitochondrial quality beyond biogenesis, which includes mitochondrial network dynamics and autophagic removal of damaged mitochondria. In addition, mitochondrial reactive oxygen species production has been suggested to regulate skeletal muscle insulin sensitivity, which may also be influenced by PGC-1α. This review aims to highlight the current evidence for PGC-1α-mediated regulation of skeletal muscle mitochondrial function beyond the effects on mitochondrial biogenesis as well as the potential PGC-1α-related impact on insulin-stimulated glucose uptake in skeletal muscle. Novelty PGC-1α regulates mitochondrial biogenesis but also has effects on mitochondrial functions beyond biogenesis. Mitochondrial quality control mechanisms, including fission, fusion, and mitophagy, are regulated by PGC-1α. PGC-1α-mediated regulation of mitochondrial quality may affect age-related mitochondrial dysfunction and insulin sensitivity.
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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 | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".