Reduced carbohydrate availability enhances exercise-induced p53 signaling in human skeletal muscle: implications for mitochondrial biogenesis
Bibliographic record
Abstract
The mechanisms that regulate the enhanced skeletal muscle oxidative capacity observed when training with reduced carbohydrate (CHO) availability are currently unknown. The aim of the present study was to test the hypothesis that reduced CHO availability enhances p53 signaling and expression of genes associated with regulation of mitochondrial biogenesis and substrate utilization in human skeletal muscle. In a repeated-measures design, muscle biopsies (vastus lateralis) were obtained from eight active males before and after performing an acute bout of high-intensity interval running with either high (HIGH) or low CHO availability (LOW). Resting muscle glycogen (HIGH, 467 ± 19; LOW, 103 ± 9 mmol/kg dry wt) was greater in HIGH compared with LOW (P < 0.05). Phosphorylation (P-) of ACC(Ser79) (HIGH, 1.4 ± 0.4; LOW, 2.9 ± 0.9) and p53(Ser15) (HIGH, 0.9 ± 0.4; LOW, 2.6 ± 0.8) was higher in LOW immediately postexercise and 3 h postexercise, respectively (P < 0.05). Before and 3 h postexercise, mRNA content of pyruvate dehydrogenase kinase 4, mitochondrial transcription factor A, cytochrome-c oxidase IV, and PGC-1α were greater in LOW compared with HIGH (P < 0.05), whereas carnitine palmitoyltransferase-1 showed a trend toward significance (P = 0.09). However, only PGC-1α expression was increased by exercise (P < 0.05), where three-fold increases occurred independently of CHO availability. We conclude that the exercise-induced increase in p53 phosphorylation is enhanced in conditions of reduced CHO availability, which may be related to upstream signaling through AMPK. Given the emergence of p53 as a molecular regulator of mitochondrial biogenesis, such nutritional modulation of contraction-induced p53 activation has implications for both athletic and clinical populations.
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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 | 0.000 |
| 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".