Respiratory muscle hemodynamic and metabolic adaptations to 16 weeks of training in varsity soccer players: near-infrared spectroscopy measurements during lung function tests (Conference Presentation)
Bibliographic record
Abstract
The purpose of this study was to test the hypothesis that mobile, wireless near-infrared spectroscopy (NIRS) instruments can be used during standard lung function tests to measure adaptations in respiratory muscle metabolism over weeks to months. In eight varsity soccer players at 0 weeks and after 16 weeks of routine training, commercially available mobile, wireless NIRS instruments were used to measure oxygenation and hemodynamics in the sternocleidomastoid (SCM, accessory inspiration muscle). During maximal expiratory pressure (MEP) and forced vital capacity (FVC) maneuvers we determined peak or antipeak changes relative to baseline in oxygenation and hemodynamics: Δ%Sat (muscle oxygen saturation), ΔtHb (total hemoglobin), ΔO2Hb (oxygenated hemoglobin), and ΔHHb (deoxygenated hemoglobin). Subjects reported that the average training load was ~13.3 h/week during the 16 study weeks, compared to ~10.4 h/week during 12 prior weeks. After 16 weeks of training compared to 0 weeks we found statistically significant increases in SCM Δ%Sat (57.7%), ΔtHb (55.3%), and ΔO2Hb (56.7%) during MEP maneuvers, and in SCM Δ%Sat (64.8%), ΔtHb (29.4%), and ΔO2Hb (51.6%) during FVC maneuvers. Our data provide preliminary evidence that NIRS measurements during standard lung function tests are sufficiently sensitive to detect improvements or declines in respiratory muscle metabolism over periods of weeks to months due to training, disease, and rehabilitation exercise.
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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 | 0.001 |
| 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".