Effect of age on O<sub>2</sub> uptake kinetics and the adaptation of muscle deoxygenation at the onset of moderate-intensity cycling exercise
Bibliographic record
Abstract
Phase 2 pulmonary O(2) uptake (Vo(2(p))) kinetics are slowed with aging. To examine the effect of aging on the adaptation of Vo(2(p)) and deoxygenation of the vastus lateralis muscle at the onset of moderate-intensity constant-load cycling exercise, young (Y) (n = 6; 25 +/- 3 yr) and older (O) (n = 6; 68 +/- 3 yr) adults performed repeated transitions from 20 W to work rates corresponding to moderate-intensity (80% estimated lactate threshold) exercise. Breath-by-breath Vo(2(p)) was measured by mass spectrometer and volume turbine. Deoxy (HHb)-, oxy-, and total Hb and/or myoglobin were determined by near-infrared spectroscopy (Hamamatsu NIRO-300). Vo(2(p)) data were filtered, interpolated to 1 s, and averaged to 5-s bins. HHb data were filtered and averaged to 5-s bins. Vo(2(p)) data were fit with a monoexponential model for phase 2, and HHb data were analyzed to determine the time delay from exercise onset to the start of an increase in HHb and thereafter were fit with a single-component exponential model. The phase 2 time constant for Vo(2(p)) was slower (P < 0.01) in O (Y: 26 +/- 7 s; O: 42 +/- 9 s), whereas the delay before an increase in HHb (Y: 12 +/- 2 s; O: 11 +/- 1 s) and the time constant for HHb after the time delay (Y: 13 +/- 10 s; O: 9 +/- 3 s) were similar in Y and O. However, the increase in HHb for a given increase in Vo(2(p)) (Y: 7 +/- 2 microM x l(-1) x min(-1); O: 13 +/- 4 microM x l(-1) x min(-1)) was greater (P < 0.01) in O compared with Y. The slower Vo(2(p)) kinetics in O compared with Y adults was accompanied by a slower increase of local muscle blood flow and O(2) delivery discerned from a faster and greater muscle deoxygenation relative to Vo(2(p)) in O.
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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".