The relationship between muscle deoxygenation and activation in different muscles of the quadriceps during cycle ramp exercise
Bibliographic record
Abstract
The relationship between muscle deoxygenation and activation was examined in three different muscles of the quadriceps during cycling ramp exercise. Seven young male adults (24 ± 3 yr; mean ± SD) pedaled at 60 rpm to exhaustion, with a work rate (WR) increase of 20 W/min. Pulmonary oxygen uptake was measured breath-by-breath, while muscle deoxygenation (HHb) and activity were measured by time-resolved near-infrared spectroscopy (NIRS) and surface electromyography (EMG), respectively, at the vastus lateralis (VL), rectus femoris (RF), and vastus medialis (VM). Muscle deoxygenation was corrected for adipose tissue thickness and normalized to the amplitude of the HHb response, while EMG signals were integrated (iEMG) and normalized to the maximum iEMG determined from maximal voluntary contractions. Muscle deoxygenation and activation were then plotted as a percentage of maximal work rate (%WR(max)). The HHb response for all three muscle groups was fitted by a sigmoid function, which was determined as the best fitting model. The c/d parameter for the sigmoid fit (representing the %WR(max) at 50% of the total amplitude of the HHb response) was similar between VL (47 ± 12% WR(max)) and VM (43 ± 11% WR(max)), yet greater (P < 0.05) for RF (65 ± 13% WR(max)), demonstrating a "right shift" of the HHb response compared with VL and VM. The iEMG also showed that muscle activation of the RF muscle was lower (P < 0.05) compared with VL and VM throughout the majority of the ramp exercise, which may explain the different HHb response in RF. Therefore, these data suggest that the sigmoid function can be used to model the HHb response in different muscles of the quadriceps; however, simultaneous measures of muscle activation are also needed for the HHb response to be properly interpreted during cycle ramp 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".