The physiological response to cold-water immersion following a mixed martial arts training session
Bibliographic record
Abstract
Combative sport is one of the most physically intense forms of exercise, yet the effect of recovery interventions has been largely unexplored. We investigated the effect of cold-water immersion on structural, inflammatory, and physiological stress biomarkers following a mixed martial arts (MMA) contest preparation training session in comparison with passive recovery. Semiprofessional MMA competitors (n = 15) were randomly assigned to a cold-water immersion (15 min at 10 °C) or passive recovery protocol (ambient air) completed immediately following a contest preparation training session. Markers of muscle damage (urinary myoglobin), inflammation/oxidative stress (urinary neopterin + total neopterin (neopterin + 7,8-dihydroneopterin)), and hypothalamic-pituitary axis (HPA) activation (saliva cortisol) were determined before, immediately after, and 1, 2, and 24 h postsession. Ratings of perceived soreness and fatigue, counter movement jump, and gastrointestinal temperature were also measured. Concentrations of all biomarkers increased significantly (p < 0.05) postsession. Cold water immersion attenuated increases in urinary neopterin (p < 0.05, d = 0.58), total neopterin (p < 0.05, d = 0.89), and saliva cortisol after 2 h (p < 0.05, d = 0.68) and urinary neopterin again at 24 h (p < 0.01, d = 0.57) in comparison with passive recovery. Perceived soreness, fatigue, and gastrointestinal temperatures were also lower for the cold-water immersion group at several time points postsession whilst counter movement jump did not differ. Combative sport athletes who are subjected to impact-induced stress may benefit from immediate cold-water immersion as a simple recovery intervention that reduces delayed onset muscle soreness as well as macrophage and HPA activation whilst not impairing functional performance.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".