Three Minutes of All-Out Intermittent Exercise per Week Increases Skeletal Muscle Oxidative Capacity and Improves Cardiometabolic Health
Bibliographic record
Abstract
We investigated whether a training protocol that involved 3 min of intense intermittent exercise per week--within a total training time commitment of 30 min including warm up and cool down--could increase skeletal muscle oxidative capacity and markers of health status. Overweight/obese but otherwise healthy men and women (n = 7 each; age = 29±9 y; BMI = 29.8±2.7 kg/m2) performed 18 training sessions over 6 wk on a cycle ergometer. Each session began with a 2 min warm-up at 50 W, followed by 3×20 s "all-out" sprints against 5.0% body mass (mean power output: ∼450-500 W) interspersed with 2 min of recovery at 50 W, followed by a 3 min cool-down at 50 W. Peak oxygen uptake increased by 12% after training (32.6±4.5 vs. 29.1±4.2 ml/kg/min) and resting mean arterial pressure decreased by 7% (78±10 vs. 83±10 mmHg), with no difference between groups (both p<0.01, main effects for time). Skeletal muscle biopsy samples obtained before and 72 h after training revealed increased maximal activity of citrate synthase and protein content of cytochrome oxidase 4 (p<0.01, main effect), while the maximal activity of β-hydroxy acyl CoA dehydrogenase increased in men only (p<0.05). Continuous glucose monitoring measured under standard dietary conditions before and 48-72 h following training revealed lower 24 h average blood glucose concentration in men following training (5.4±0.6 vs. 5.9±0.5 mmol/L, p<0.05), but not women (5.5±0.4 vs. 5.5±0.6 mmol/L). This was associated with a greater increase in GLUT4 protein content in men compared to women (138% vs. 23%, p<0.05). Short-term interval training using a 10 min protocol that involved only 1 min of hard exercise, 3x/wk, stimulated physiological changes linked to improved health in overweight adults. Despite the small sample size, potential sex-specific adaptations were apparent that warrant further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".