Sprint interval and traditional endurance training induce similar improvements in peripheral arterial stiffness and flow-mediated dilation in healthy humans
Bibliographic record
Abstract
Low-volume sprint interval training (SIT), or repeated sessions of brief, intense intermittent exercise, elicits metabolic adaptations that resemble traditional high-volume endurance training (ET). The effects of these different forms of exercise training on vascular structure and function remain largely unexplored. To test the hypothesis that SIT and ET would similarly improve peripheral artery distensibility and endothelial function and central artery distensibility, we recruited 20 healthy untrained subjects (age: 23.3 +/- 2.8 yr) and had them perform 6 wk of SIT or ET (n = 5 men and 5 women per group). The SIT group completed four to six 30-s "all-out" Wingate tests separated by 4.5 min of recovery 3 days/wk. The ET group completed 40-60 min of cycling at 65% of their peak oxygen uptake (Vo2peak) 5 days/wk. Popliteal endothelial function, both relative and normalized to shear stimulus, was improved after training in both groups (main effect for time, P < 0.05). Carotid artery distensibility was not statistically altered by training (P = 0.29) in either group; however, popliteal artery distensibility was improved in both groups to the same degree (main effect, P < 0.05). We conclude that SIT is a time-efficient strategy to elicit improvements in peripheral vascular structure and function that are comparable to ET. However, alterations in central artery distensibility may require a longer training stimuli and/or greater initial vascular stiffness than observed in this group of healthy subjects.
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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".