Oxygen uptake kinetics in endurance-trained and untrained postmenopausal women
Bibliographic record
Abstract
The rate of adjustment for pulmonary oxygen uptake (τV̇O(2p)) is slower in untrained and in older adults. Near-infrared spectroscopy (NIRS) has shed light on potential mechanisms underlying this in young men and women and in older men; however, there is no such data available in older women. The purpose of this study was to gain a better understanding of the mechanisms of slower τV̇O(2p) in older women who were either endurance-trained or untrained. Endurance-trained (n = 10; age, 62.6 ± 1.0 years) and untrained (n = 9; age, 69.1 ± 2.2 years) older women attended 2 maximal and 2 submaximal (90% of ventilatory threshold) exercise sessions. Oxygen uptake (V̇O(2)) was measured breath by breath, using a mass spectrometer, and changes in deoxygenated hemoglobin concentration of the vastus lateralis ([HHb]) were measured using NIRS. Heart rate was measured continuously with a 3-lead electrocardiogram. τV̇O(2p) was faster in trained (35.1 ± 5.5 s) than in untrained (57.0 ± 8.1 s) women. The normalized [HHb] to V̇O(2) ratio, an indicator of muscle O(2) delivery to O(2) utilization, indicated a smaller overshoot in trained (1.09 ± 0.1) than in untrained (1.39 ± 0.1) women. Heart rate data indicated a faster adjustment of heart rate in trained (33.0 ± 13.0) than in untrained (68.7 ± 14.1) women. The pairing of V̇O(2p) data with NIRS-derived [HHb] data indicates that endurance-trained older women likely have better matching of O(2) delivery to O(2) utilization than older untrained women during moderate-intensity exercise, leading to a more rapid adjustment of V̇O(2p).
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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".