Peroxisome proliferator‐activated receptor γ coactivator 1α regulates mitochondrial calcium homeostasis, sarcoplasmic reticulum stress, and cell death to mitigate skeletal muscle aging
Bibliographic record
Abstract
Age-related impairment of muscle function severely affects the health of an increasing elderly population. While causality and the underlying mechanisms remain poorly understood, exercise is an efficient intervention to blunt these aging effects. We thus investigated the role of the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a potent regulator of mitochondrial function and exercise adaptation, in skeletal muscle during aging. We demonstrate that PGC-1α overexpression improves mitochondrial dynamics and calcium buffering in an estrogen-related receptor α-dependent manner. Moreover, we show that sarcoplasmic reticulum stress is attenuated by PGC-1α. As a result, PGC-1α prevents tubular aggregate formation and cell death pathway activation in old muscle. Similarly, the pro-apoptotic effects of ceramide and thapsigargin were blunted by PGC-1α in muscle cells. Accordingly, mice with muscle-specific gain-of-function and loss-of-function of PGC-1α exhibit a delayed and premature aging phenotype, respectively. Together, our data reveal a key protective effect of PGC-1α on muscle function and overall health span in aging.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".