Mitochondrial function and protein expression profile in skeletal muscle from PGC‐1α null mice
Bibliographic record
Abstract
PPAR‐gamma coactivator‐1α (PGC‐1α) is an important regulator of mitochondrial biogenesis. However, its effect on mitochondrial function, key regulatory proteins involved in organelle synthesis and apoptosis are not resolved in skeletal muscle, particularly in intermyofibrillar (IMF) and subsarcolemmal (SS) subfractions. Thus, we examined respiration, ROS production and protein expression in mitochondria from PGC‐1α null animals. SS and IMF mitochondrial yields in muscle from PGC‐1α null animals was 36% and 27% (p<0.05) lower, than in wild‐type animals. Parallel decrements of 22% and 36% (p<0.05) existed in the mitochondrial markers, COX activity and cytochrome c. Despite these differences, the mtDNA transcription factor Tfam, and mitochondrial fission protein Fis1, were similar in null and wild‐type animals. However, the import protein mtHSP70 was 30% lower in muscle from PGC‐1α null animals. The Bax:Bcl‐2 ratio, an apoptotic indicator, was unaltered but both proteins were 35% greater in muscle from PGC‐1α null animals. SS mitochondria from PGC‐1α null animals displayed 35% and 20% lower respiration rates and ROS production, respectively, while IMF mitochondria exhibited no differences compared to wild‐type. Thus, the absence of PGC‐1α does not completely reduce mitochondrial content and must evoke compensatory mechanisms to prevent the entire loss of mitochondrial function in muscle.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".