Extremely low-volume, high-intensity interval training improves exercise capacity and increases mitochondrial protein content in human skeletal muscle
Bibliographic record
Abstract
Purpose: The purpose of the present study was to evaluate whole-muscle content of several proteins involved in the regulation of skeletal muscle mitochondrial protein content and anaerobic capacity following 4 weeks of extremely low-volume high-intensity interval training (HIT). Methods: Young, healthy, recreationally active adult males (n = 8) trained 4 times a week for 4 weeks on a cycle ergometer. Each session involved 4 min of total exercise comprised of eight 20 s intervals at ~170% of peak aerobic power separated by 10 s rest. Muscle biopsies were taken prior to (pre) and ~72 hrs post-training (post). Par- ticipants completed an incremental peak oxygen up- take (VO2peak) test and a Wingate test pre-, mid-, and post-training. Results: VO2peak was elevated (p p -1·min-1, mid: 43.4 ± 2.5 ml·kg-1·min-1, post-: 47.2 ± 2.9 ml·kg-1·min-1). Wingate mean power also increased with training (pre-: 701.0 ± 73.0 W, mid-: 745.5 ± 73.3 W, post-: 786.8 ± 80.0 W). While maximal citrate synthase activity was unchanged, protein expression of the mitochondrial protein cytochrome c oxidase (COX) subunit I (+27%; p p p = 0.08) increased. Increases (p α (+19%), and nuclear PGC-1α (+46%) were also observed after 4 weeks of HIT. No changes were observed in the whole-muscle contents of PDHe1a, PDK4, SIRT1, mTOR, S6K1, MCT1, or PFK protein. Conclusions: These results demonstrate that several mitochondrial protein (but not citrate synthase activity), PGC-1α protein content, and exercise capacity can be improved in only 4 min of total training time per day, 4 days per wk using HIT cycle training.
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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) | 0.002 | 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".