Effects of short-term endurance training on muscle deoxygenation trends using NIRS
Bibliographic record
Abstract
PURPOSE: This study examined changes in cardiorespiratory responses and muscle deoxygenation trends to test the hypothesis that both central and peripheral adaptations would contribute to the improvements in VO(2max) and simulated cycling performance after short-term high-intensity training. METHODS: Eight male cyclists performed an incremental cycle ergometer test to voluntary exhaustion, and a simulated 20-km time trial (20TT) on wind-loaded rollers before and after training (60 min x 5 d x wk(-1) x 3 wk at 85-90% VO(2max). Near-infrared spectroscopy (NIRS) was used to evaluate the trend in vastus medialis hemoglobin/myoglobin deoxygenation (Hb/Mb-O(2) during both tests pre- and post-training. RESULTS: Training induced significant increases (P </= 0.05) in maximal power output (367 +/- 63 to 383 +/- 60 W), VO(2max) (4.39 +/- 0.66 to 4.65 +/- 0.57 L x min(-1)), and maximal O(2) pulse (22.7 +/- 3.2 to 24.6 +/- 2.8 mL O(2) x beat(-1)) during the incremental test, but maximal muscle deoxygenation was unchanged. 20TT performance was significantly faster (27:32 +/- 1:43 to 25:46 +/- 1:44 min:s; P </= 0.05) after training without a significant increase (P > 0.05) in the VO(2) (4.02 +/- 0.52 to 4.04 +/- 0.51), heart rate (176 +/- 9 to 173 +/- 8 beats x min ) or O pulse (22.4 +/- 3.2 to 23.5 +/- 2.8 mL O(2) x beat(-1)). However, mean muscle deoxygenation during the 20TT was significantly lower after training (-550 +/- 292 to -707 +/- 227 mV, P </= 0.05), and maximal deoxygenation showed a trend toward significance (-807 +/- 344 to -1,009 +/- 331 mV, P = 0.08), suggesting a greater release of oxygen from Hb/Mb-O(2) via the Bohr effect. CONCLUSION: The significant improvement in VO(max) induced by short-term endurance training in well-trained cyclists was due primarily to central adaptations, whereas the simulated 20TT performance was enhanced due to localized changes in muscle oxygenation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".