Oxygen Uptake Dynamics Conform to Acute Changes in Muscle Excitation and Total Hemoglobin Concentration during Constant Work Rate Exercise
Bibliographic record
Abstract
PURPOSE: This study aimed to investigate whether muscle excitation during constant-work rate (WR) cycling is connected with total[Hb + Mb] and whether they interact with the oxygen uptake (V̇O 2 ) dynamics. METHODS: In experiment 1, 10 participants performed a 21-min constant-WR (CWR) within the heavy-intensity domain (i.e., 75% of the difference between the gas exchange threshold and the maximal metabolic steady state) and a ramp-to-constant-WR (rCWR) to the same WR. CWR and rCWR were repeated twice and allocated in random order. In experiment 2, nine participants performed a double-constant-WR (dCWR) consisting of a 21-min exercise bout, a short 20-s break, and a second bout of 21 min within the heavy domain. V̇O 2 , EMG root-mean-square (EMG RMS ), total[Hb + Mb], and deoxygenated hemoglobin ([HHb]) were collected from the vastus lateralis. The EMG RMS /total[Hb + Mb] and the EMG RMS /[HHb] ratios were computed. RESULTS: The EMG RMS was lower at minutes 1 and 7 and total[Hb + Mb] higher at minute 1 during the rCWR compared with the CWR condition (all P < 0.05). EMG RMS displayed an overshoot at minute 1, which was different from minute 21 during the CWR condition ( P < 0.05). EMG RMS did not display an overshoot after the 20-s break during the dCWR condition. The EMG RMS /total[Hb + Mb] inverted ratio was not different from V̇O 2 (%). The EMG magnitude of frequencies ranging from ~30 to 90 Hz was initially higher and decreased over time ( P < 0.05). CONCLUSIONS: This study demonstrated that EMG RMS -derived muscle excitation can be reduced by exercise protocols that promote higher total[Hb + Mb]. Furthermore, the interaction between muscle excitation and total[Hb + Mb] matched with systemic V̇O 2 .
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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".