Exercise intensity modulates the appearance of circulating microvesicles with proangiogenic potential upon endothelial cells
Bibliographic record
Abstract
The effect of endurance exercise on circulating microvesicle dynamics and their impact on surrounding endothelial cells is unclear. Here we tested the hypothesis that exercise intensity modulates the time course of platelet (PMV) and endothelial-derived (EMV) microvesicle appearance in the circulation through hemodynamic and biochemical-related mechanisms, and that microvesicles formed during exercise would stimulate endothelial angiogenesis in vitro. Nine healthy young men had venous blood samples taken before, during, and throughout the recovery period after 1 h of moderate [46 ± 2% maximal oxygen uptake (V̇o 2max )] or heavy (67 ± 2% V̇o 2max ) intensity semirecumbent cycling and a time-matched resting control trial. In vitro experiments were performed by incubating endothelial cells with rest and exercise-derived microvesicles to examine their effects on cell angiogenic capacities. PMVs (CD41 + ) increased from baseline only during heavy exercise (from 21 ± 1 × 10 3 to 55 ± 8 × 10 3 and 48 ± 6 × 10 3 PMV/μl at 30 and 60 min, respectively; P < 0.05), returning to baseline early in postexercise recovery ( P > 0.05), whereas EMVs (CD62E + ) were unchanged ( P > 0.05). PMVs were related to brachial artery shear rate ( r 2 = 0.43) and plasma norepinephrine concentrations ( r 2 = 0.21) during exercise ( P < 0.05). Exercise-derived microvesicles enhanced endothelial proliferation, migration, and tubule formation compared with rest microvesicles ( P < 0.05). These results demonstrate substantial increases in circulating PMVs during heavy exercise and that exercise-derived microvesicles stimulate human endothelial cells by enhancing angiogenesis and proliferation. This involvement of microvesicles may be considered a novel mechanism through which exercise mediates vascular healing and adaptation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".