Brief intense interval exercise activates AMPK and p38 MAPK signaling and increases the expression of PGC-1α in human skeletal muscle
Bibliographic record
Abstract
From a cell signaling perspective, short-duration intense muscular work is typically associated with resistance training and linked to pathways that stimulate growth. However, brief repeated sessions of sprint or high-intensity interval exercise induce rapid phenotypic changes that resemble traditional endurance training. We tested the hypothesis that an acute session of intense intermittent cycle exercise would activate signaling cascades linked to mitochondrial biogenesis in human skeletal muscle. Biopsies (vastus lateralis) were obtained from six young men who performed four 30-s “all out” exercise bouts interspersed with 4 min of rest (<80 kJ total work). Phosphorylation of AMP-activated protein kinase (AMPK; subunits α1 and α2) and the p38 mitogen-activated protein kinase (MAPK) was higher ( P ≤ 0.05) immediately after bout 4 vs. preexercise. Peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) mRNA was increased approximately twofold above rest after 3 h of recovery ( P ≤ 0.05); however, PGC-1α protein content was unchanged. In contrast, phosphorylation of protein kinase B/Akt (Thr308 and Ser473) tended to decrease, and downstream targets linked to hypertrophy (p70 ribosomal S6 kinase and 4E binding protein 1) were unchanged after exercise and recovery. We conclude that signaling through AMPK and p38 MAPK to PGC-1α may explain in part the metabolic remodeling induced by low-volume intense interval exercise, including mitochondrial biogenesis and an increased capacity for glucose and fatty acid oxidation.
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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".