The Impact of Different Exercise Intensities on Vasodilation and Shear Rate Patterns in Children
Bibliographic record
Abstract
PURPOSE: The effect of exercise intensity on vasodilator function is poorly understood in children. The authors compared the acute effect of high-intensity interval exercise (HIIE) with moderate-intensity steady-state exercise (MISS) on postexercise vasodilation and shear patterns in 7- to 12- year-old children. METHODS: Superficial femoral artery diameter, shear rates, and flow-mediated dilation were measured pre, immediately following (post), and 1 hour after (post60) HIIE (six 1-min sprints at 90% peak power [Wmax], with 1-min recovery) and MISS (15 min at 44% Wmax). RESULTS: Baseline superficial femoral artery diameter increased similarly following both HIIE (pre 4.23 [0.41] mm, post 4.73 [0.56] mm) and MISS (pre 4.28 [0.56] mm, post 4.59 [0.64] mm), returning to preexercise values post60. Blood flow and antegrade shear rate were increased post HIIE and MISS, but to a greater extent, post HIIE (P < .05). Retrograde shear rate was attenuated post both exercise conditions and remained post60 (P < .001). There was a decline in flow-mediated dilation postexercise (HIIE Δ -2.9%; MISS Δ -2.4%), which was no longer apparent when corrected for baseline diameter. CONCLUSION: Acute bouts of external work-matched HIIE or MISS exert a similar impact on shear-mediated conduit artery vasodilation and flow-mediated dilation in children, and this is reversed 1 hour after exercise.
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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 | 0.001 |
| 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".