The Effect of High Intensity Interval Training Versus Steady State Aerobic Training on Skin Microvascular Reactivity in Moderately Active Young Adults: A Pilot Study
Bibliographic record
Abstract
A sedentary lifestyle is associated with endothelial dysfunction, leading to vascular pathology and impaired microvascular reactivity (MVR). Enhanced endothelial functioning has been seen in aerobically trained individuals. The purpose of this study was to determine if there was a differential training response of skin MVR in response to high intensity aerobic interval training (HIAIT) as compared to steady state aerobic training (SSAT). The study involved 16 moderately active male students (age: 20.93 ± 5.05 yrs). They were randomly assigned to one of three groups; HIAIT, SSAT, and control group (CG). Baseline testing was performed to determine the VO2max, lactate threshold, blood pressure, body composition and a post-occlusive reactive hyperemia response (PORH) test was used to assess microvascular reactivity on the right palmer forearm using a moorVMS-Laser Doppler Flowmetry (LDF) These parameters were reassessed after three weeks (mid-point) and six-weeks (post intervention) weeks. Statistical significance was set at p≤0.05. There were no significant interactions between the variables measured in the three groups over time. There was a positive linear relationship in the SSAT group for PORHmax/time to peak (Tp) at baseline (r = 0.998, p = 0.039), midpoint (r = 0.992, p = 0.083), and the post intervention (r = 0.987, p = 0.103). Training in the SSAT group had improved PORHpeak at midpoint and post intervention time points (r = 0.999, p = 0.22; r = 1, p = 0.006; r = 1, p = 0.011). Training in either the HIAIT or the SSAT group had no significant effect on skin MVR in moderately active young adults. SSAT did display a positive linear relationship with PORHmax/Tp, and PORHpeak, which are variables influencing skin MVR.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".