High-intensity interval training followed by postexercise cold-water immersion does not alter angiogenic circulating cells, but increases circulating endothelial cells
Bibliographic record
Abstract
High-intensity interval training (HIIT) induces vascular adaptations that might be attenuated by postexercise cold-water immersion (CWI). Circulating angiogenic cells (CAC) participate in the vascular adaptations and circulating endothelial cells (CEC) indicate endothelial damage. CAC and CEC are involved in vascular adaptation. Therefore, the aim of the study was to investigate postexercise CWI during HIIT on CAC and CEC and on muscle angiogenesis-related molecules. Seventeen male subjects performed 13 HIIT sessions followed by 15 min of passive recovery (n = 9) or CWI at 10 °C (n = 8). HIIT comprised cycling (8–12 bouts, 90%–110% peak power). The first and the thirteenth sessions were similar (8 bouts at 90% of peak power). Venous blood was drawn before exercise (baseline) and after the recovery strategy (postrecovery) in the first (pretraining) and in the thirteenth (post-training) sessions. For CAC and CEC identification lymphocyte surface markers (CD133, CD34, and VEGFR2) were used. Vastus lateralis muscle biopsies were performed pre- and post-training for protein (p-eNOS ser1177 ) and gene (VEGF and HIF-1) expression analysis related to angiogenesis. CAC was not affected by HIIT or postexercise CWI. Postexercise CWI increased acute and baseline CEC number. Angiogenic protein and genes were not differently modulated by post-CWI. HIIT followed by either recovery strategy did not alter CAC number. Postexercise CWI increased a marker of endothelial damage both acutely and chronically, suggesting that this postexercise recovery strategy might cause endothelial damage. Novelty HIIT followed by CWI did not alter CAC. HIIT followed by CWI increased CEC. Postexercise CWI might cause endothelial damage.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".