AMPK and PGC-<i>α</i> following maximal and supramaximal exercise in men and women: a randomized cross-over study
Bibliographic record
Abstract
We tested the hypothesis that AMPK activation and peroxisome proliferator gamma coactivator 1 alpha (PGC-1 α) expression are not augmented as exercise intensity (power output) increases from maximal to supramaximal intensities and conducted an exploratory analysis comparing AMPK activation and PGC-1α expression in males and females. Seventeen ( n = 9 males; n = 8 females) recreationally active, healthy, young individuals volunteered to participate in the current study. Participants completed work matched interval exercise at 100% (Max) and 133% (Supra) of peak work rate (WRpeak). Intervals were 1 min in duration and participants were prescribed 6 and 8 intervals of Max and Supra, respectively, to equate external work across protocols. PGC-1 α mRNA expression and activation of AMPK (p-ACC) were examined in muscle biopsy samples. Interval WR (watts; W), intensity (%WRpeak) and average HR (bpm), blood lactate (mmol/L) and rating of perceived exertion were all higher (all p < 0.05) in Supra. Fatigue was greater ( p < 0.05) in Supra. PGC-1α mRNA expression significantly increased after exercise in Max ( p < 0.01) and Supra ( p < 0.01), but was not significantly different ( p = 0.71) between intensities. A main effect of time (Pre – 0 h) ( p < 0.01) was observed for p-ACC; however, no effect of intensity ( p = 0.08) or interaction ( p = 0.97) was observed. No significant effects of time ( p = 0.05) intensity ( p = 0.42), or interaction ( p = 0.97) were observed for p-AMPK (Thr172). Exploratory sex analysis demonstrated a main effect of sex for p-ACC (greater p-ACC in males; p < 0.05) but not for p-AMPK or PGC-1 α expression. Our results confirm that AMPK-PGC-1 α signalling is not augmented following supramaximal exercise and provide novel data demonstrating a decrease in AMPK activation (p-ACC) in females compared to men. Trial registration: https://doi.org/10.17605/OSF.IO/U7PX9 .
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".