Cardiorespiratory alterations induced by low-intensity exercise performed in water or on land
Bibliographic record
Abstract
The aim of this study was to compare the cardiorespiratory alterations induced by a low-intensity exercise performed on land or in water. Sixteen healthy subjects were investigated. The exercise consisted of a 1-h period of ergocycling at 35%-40% of peak oxygen uptake. Investigations were performed at rest and 45 min after the beginning of the exercises. Hemodynamic changes were studied by Doppler-echocardiography. Gas exchanges were continuously monitored by an oxygen gas analyzer. Blood samples were taken successively at baseline, within the last minutes of the exercise bout, and during recovery to measure total protein concentration and natriuretic peptides. Cardiovascular parameters were not significantly different during exercise performed on land or in water. As a result of an accelerated breathing frequency, ventilation output was significantly greater in water. Biological changes included a decrease in total protein concentration and an increase in natriuretic peptides in water. During low-intensity exercise, ventilatory alterations favoured increasing the work of breathing while in the water when compared with the same exercise performed on land. Hemodynamic changes were similar in the 2 conditions. Furthermore, biological findings suggest that the fluid transfer from intravascular sector toward interstitial sector could be facilitated in water.
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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".