Post-exercise endothelial function is not associated with extracellular vesicle release in healthy young males
Bibliographic record
Abstract
Acute exercise can result in temporary decrease in endothelial functions, which may represent a transient period of risk. Numerous mechanisms underpinning these responses included release of extracellular vesicles (EVs) derived from apoptotic or activated endothelial cells and platelets. This study aims to compare the time course of endothelial responses to moderate-intensity continuous exercise (MICE) and high-intensity interval exercise (HIIE) and the associations with EV release. Eighteen young healthy males (age: 22.6 ± 3.7 years, BMI: 25.6 ± 2.5 m2/kg, and VO2peak: 38.6 ± 6.5 mL/kg/min) completed two randomly assigned exercises: HIIE (10 × 1 min-@-90% heart rate reserve (HRR) and 1 min passive recovery) and MICE (30 min-@-70% HRR) on a cycle ergometer. Flow-mediated dilation (FMD) was used to assess endothelial function and blood samples were collected to evaluate endothelial cell-derived EV (CD62E+) and platelet-derived EV (CD41a+), 10, 60, and 120 min before and after exercise. There were similar increases but different time courses ( P = 0.017) in FMD (increased 10 min post-HIIE, P < 0.0001 and 60 min post-MICE, P = 0.038). CD62E+ remained unchanged ( P = 0.530), whereas overall CD41a+ release was reduced 60 min post-exercise ( P = 0.040). FMD was not associated with EV absolute release or change ( P > 0.05). Acute exercise resulted in similar improvements, but different time course in FMD following either exercise. Whilst EVs were not associated with FMD, the reduction in platelet-derived EVs may represent a protective mechanism following acute 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 | 0.000 |
| 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".