Effects of exercise during water immersion on arterial function in humans
Bibliographic record
Abstract
Flow-mediated dilation (FMD) provides a valid bioassay of vascular function in humans. Although water immersion induces hemodynamic effects that modify brachial artery shear stress, it is unclear whether water-based exercise modifies FMD. We hypothesized that exercise in 32°C water would decrease brachial artery shear and FMD relative to land-based exercise, whereas exercise in 38°C would increase brachial shear and FMD. Ten healthy participants (8 males; 23.9 ± 3.3 yr) completed 30 min of resistance-matched cycle exercise in three separate conditions: on land and in 32°C and 38°C water. Brachial artery shear rate area under the curve (SRAUC) was measured throughout each condition, with FMD measured pre- and postexercise. Brachial SRAUC increased during exercise in all conditions and was highest across the 38°C condition compared with Land and 32°C conditions (38°C: 27,507 ± 8,350 vs. Land: 9,908 ± 4,738 vs. 32°C: 13,840 ± 5,861 1/s, P < 0.001). Retrograde diastolic shear was greater during 32°C than both Land and 38°C conditions (32°C:−3,869 ± 2,198 vs. Land:−1,602 ± 1,334 vs. 32°C:−1,036 ± 1,754, P < 0.01). FMD increased as a result of 38°C (6.2 ± 1.9 vs. 8.5 ± 2.7%, P = 0.03), with no change in the Land exercise (6.3 ± 2.4 vs. 7.7 ± 2.4%, P = 0.10) or 32°C condition (6.4 ± 3.2 vs. 6.7 ± 3.2%, P = 0.99). Our findings indicate that cycle exercise in hot water attenuates retrograde shear, increases antegrade shear, and FMD. Exercise in 32°C water induces central hemodynamic changes relative to land-based exercise, but these do not translate to increases in FMD in either condition, likely due to the impact of increased retrograde shear. Our findings indicate that modification of shear has direct acute impacts on endothelial function in humans.
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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".