Adaptation of pulmonary O<sub>2</sub> uptake kinetics and muscle deoxygenation at the onset of heavy-intensity exercise in young and older adults
Bibliographic record
Abstract
The purpose was to examine the adaptation of pulmonary O(2) uptake (Vo(2p)) and deoxygenation of the vastus lateralis muscle at the onset of heavy-intensity, constant-load cycling exercise in young (Y; 24 +/- 4 yr; mean +/- SD; n = 5) and older (O; 68 +/- 3 yr; n = 6) adults. Subjects performed repeated transitions on 4 separate days from 20 W to a work rate corresponding to heavy-intensity exercise. Vo(2p) was measured breath by breath. The concentration changes in oxyhemoglobin, deoxyhemoglobin (HHb), and total hemoglobin/myoglobin were determined by near-infrared spectroscopy (Hamamatsu NIRO-300). Vo(2p) data were filtered, interpolated to 1 s, and averaged to 5-s bins. HHb-near-infrared spectroscopy data were filtered and averaged to 5-s bins. A monoexponential model was used to fit Vo(2p) [phase 2, time constant (tau) of Vo(2p)] and HHb [following the time delay (TD) from exercise onset to the start of an increase in HHb] data. The tauVo(2p) was slower (P < 0.001) in O (49 +/- 8 s) than Y (29 +/- 4 s). The HHb TD was similar in O (8 +/- 3 s) and Y (7 +/- 1 s); however, the tau HHb following TD was faster (P < 0.05) in O (8 +/- 2 s) than Y (14 +/- 2 s). The slower Vo(2p) kinetics and faster muscle deoxygenation in O compared with Y during heavy-intensity exercise imply that the kinetics of muscle perfusion are slowed relatively more than those of Vo(2p) in O. This suggests that the slowed Vo(2p) kinetics in O may be a consequence of a slower adaptation of local muscle blood flow relative to that in Y.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".