Cold‐water immersion decreases cerebral oxygenation but improves recovery after intermittent‐sprint exercise in the heat
Bibliographic record
Abstract
This study examined the effects of post-exercise cooling on recovery of neuromuscular, physiological, and cerebral hemodynamic responses after intermittent-sprint exercise in the heat. Nine participants underwent three post-exercise recovery trials, including a control (CONT), mixed-method cooling (MIX), and cold-water immersion (10 °C; CWI). Voluntary force and activation were assessed simultaneously with cerebral oxygenation (near-infrared spectroscopy) pre- and post-exercise, post-intervention, and 1-h and 24-h post-exercise. Measures of heart rate, core temperature, skin temperature, muscle damage, and inflammation were also collected. Both cooling interventions reduced heart rate, core, and skin temperature post-intervention (P < 0.05). CWI hastened the recovery of voluntary force by 12.7 ± 11.7% (mean ± SD) and 16.3 ± 10.5% 1-h post-exercise compared to MIX and CONT, respectively (P < 0.01). Voluntary force remained elevated by 16.1 ± 20.5% 24-h post-exercise after CWI compared to CONT (P < 0.05). Central activation was increased post-intervention and 1-h post-exercise with CWI compared to CONT (P < 0.05), without differences between conditions 24-h post-exercise (P > 0.05). CWI reduced cerebral oxygenation compared to MIX and CONT post-intervention (P < 0.01). Furthermore, cooling interventions reduced cortisol 1-h post-exercise (P < 0.01), although only CWI blunted creatine kinase 24-h post-exercise compared to CONT (P < 0.05). Accordingly, improvements in neuromuscular recovery after post-exercise cooling appear to be disassociated with cerebral oxygenation, rather reflecting reductions in thermoregulatory demands to sustain force production.
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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".