Effect of repeated sprint training in hypoxia on acute and chronic redox balance modulation
Bibliographic record
Abstract
Little is known regarding the effects high-intensity training performed in hypoxia on the oxidative stress and antioxidant systems. The aim of this study was to assess the potential effect of 4 weeks of repeated sprint training in hypoxia (RSH) on the redox balance. Forty male well-trained cyclists were matched into two different interventions (RSH, n = 20) or in normoxia, RSN, n = 20) and tested twice (before (Pre-) and after (Post-) a 4-week of training) for performance (repeated sprint ability (RSA) test), oxidative stress, and antioxidant status. Antioxidant enzyme activity (Superoxide Dismutase, Glutathione Peroxidase, and catalase), NO metabolites (NOx: nitrites and nitrates), ferric reducing antioxidant power, Malondialdehyde (MDA), nitrotyrosine, and carbonyls were measured in plasma. At Post-, MDA, and carbonyls increased (p < 0.05) in the RSN group both at rest (+90.6%) and also acutely in response to RSA (+22.9%); but not in RSH. At Post-, in the RSH group, catalase increased (p < 0.05) both at rest (+44.7%) and in response to the RSA test (+66.3%). At Post-, SOD, and nitrotyrosine decreased after RSA and at rest, regardless of the group (p = 0.0012 and p = 0.0413, respectively). At Post-, NOx decreased after the RSA test, regardless of the group (p < 0.05). In conclusion, several weeks of RSH training limits the increase in oxidative stress markers both at rest and in response to RSA test. Moreover, such training downregulated SOD activity, possibly due to an overproduction of reactive oxygen species. These findings could constitute a paradigm shift with a better enzymatic adaptation after RSH concomitant with a distinct reactive oxygen species (ROS) production between RSH and RSN.
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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".