Determinants of Oxygen Uptake Kinetics in Older Humans Following Single‐Limb Endurance Exercise Training
Bibliographic record
Abstract
We hypothesised that the observed acceleration in the kinetics of exercise on-transient oxygen uptake (VO2) of five older humans (77 +/- 7 years (mean +/- S.D.) following 9 weeks of single-leg endurance exercise training was due to adaptations at the level of the muscle cell. Prior to, and following training, subjects performed constant-load single-limb knee extension exercise. Following training VO2 kinetics (phase 2, tau) were accelerated in the trained leg (week 0, 92 +/- 44 s; week 9, 48 +/- 22 s) and unchanged in the untrained leg (week 0, 104 +/- 43 s; week 9, 126 +/- 35 s). The kinetics of mean blood velocity in the femoral artery were faster than the kinetics of VO2, but were unchanged in both the trained (week 0, 19 +/- 10 s; week 9, 26 +/- 11 s) and untrained leg (week 0, 20 +/- 18 s; week 9, 18 +/- 10 s). Maximal citrate synthase activity, measured from biopsies of the vastus lateralis muscle, increased (P < 0.05) in the trained leg (week 0, 6.7 +/- 2.0 micromol x (g wet wt)(-1) x min(-1); week 9, 11.4 +/- 3.6 micromol x (g wet wt)(-1) x min(-1)) but was unchanged in the untrained leg (week 0, 5.9 +/- 0.5 micromol x (g wet wt)(-1) x min(-1); week 9, 7.9 +/- 1.9 micromol x (g wet wt)(-1) x min(-1)). These data suggest that the acceleration of VO2 kinetics was due to an improved rate of O2 utilisation by the muscle, but was not a result of increased O2 delivery.
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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 | 0.000 |
| 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".