EFFECT OF HYPERBARIC OXYGEN ON VENOUS PO2, PTCO2 AND VO2MAX IN A NORMOBARIC ENVIRONMENT
Bibliographic record
Abstract
Several studies have examined the use of HBO2 prior to exercise in order to alter performance. It is unclear if a single HBO2 treatment can improve performance. The purpose of this study was to examine venous PO2, transcutaneous tissue PO2 (PtcO2), and VO2max in a normobaric environment following a single HBO2 treatment. Ten moderately trained (VO2max = 57.6 mL/kgmin) males volunteered for the study. Baseline testing included measures of VO2max, PtcO2, and anthropometry. Subjects received two HBO2 treatments, which consisted of breathing 95% oxygen at 2.5 ATA for 90 min. Following the first HBO2 treatment (6.0 ± 1.0 min), subjects performed a VO2max test. Following the second HBO2 treatment, leg and chest PtcO2 and venous PO2 were monitored for 60 min. The results showed that VO2max, running time, and peak La were not altered (p < 0.05) post-HBO2 treatment. Leg PtcO2 was lower (p < 0.05) and chest PtcO2 was unchanged following the HBO2 treatment compared to baseline values. Venous PO2 was lower in the first 3 min post-HBO2 treatment than subsequent values, but no other differences were found (p < 0.05). The results of this study show that a single HBO2 treatment at 2.5 ATA for 90 min does not elevate venous PO2, PtcO2, or VO2max in a normobaric, normoxic environment.
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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".