Impact Of High-Intensity Interval Training On Popliteal Vascular Responses To Prolonged Sitting
Bibliographic record
Abstract
Prolonged, uninterrupted sitting (≥1-h) impairs lower-limb flow-mediated dilation (FMD), nitroglycerin-mediated dilation (NMD) and resistance vessel responses. The benefits of regular aerobic exercise on lower-limb vascular health are well established. However, there is conflicting evidence regarding the impact of aerobic fitness level on sitting induced-reductions in lower-limb arterial function. PURPOSE: To explore the impact that 12-weeks of high-intensity interval training (HIIT, 3 sessions/week) had on popliteal FMD, NMD, and reactive hyperemic responses to a bout of prolonged sitting. METHODS: 9 young, healthy adults were randomly assigned to HIIT (n = 5, 4 females; 23 ± 2 yrs) or Control groups (n = 4, 2 females; 22 yrs). Relative FMD responses (% peak increase from baseline diameter) to 5-min distal cuff occlusion (250 mmHg) and relative NMD responses (% peak increase from baseline diameter) to sublingual nitroglycerin administration (0.4 mg), as well as post-occlusive peak blood flow (mL/min) were assessed via duplex ultrasonography before and after a ~ 3-h bout of uninterrupted sitting. These assessments were repeated following the HIIT (2 × 20-min bouts of alternating between 15-s intervals at 100% of peak aerobic power and passive recovery) or Control (habitual physical activity) periods. Sitting-induced changes in arterial function were then compared before and after each period. RESULTS: There were no between-group differences (all, P > 0.18) in sitting-induced popliteal FMD (HIIT: -2.5 ± 2.7% to -1.9 ± 2.0%; Control: -2.8 ± 1.3% to -2.8 ± 3.0%), NMD (HIIT: -3.6 ± 2.5% to -3.3 ± 2.4%; Control: -2.6 ± 2.1 to -4.4 ± 2.4%), or peak hyperemic responses (HIIT: -150 ± 161 to -367 ± 212 mL/min; Control: -262 ± 133 to -257 ± 222 mL/min). CONCLUSION: These results indicate that a 12-week HIIT intervention did not provide protection against prolonged sitting-induced lower-limb vascular dysfunction.
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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".