Time course and mechanisms of adaptations in cardiorespiratory fitness with endurance training in older and young men
Bibliographic record
Abstract
The time-course and mechanisms of adaptation of cardiorespiratory fitness were examined in 8 older (O) (68 +/- 7 yr old) and 8 young (Y) (23 +/- 5 yr old) men pretraining and at 3, 6, 9, and 12 wk of training. Training was performed on a cycle ergometer three times per week for 45 min at approximately 70% of maximal oxygen uptake (Vo(2 max)). Vo(2 max) increased within 3 wk with further increases observed posttraining in both O (+31%) and Y (+18%), (P < 0.05). Maximal cardiac output (Q(max), open-circuit acetylene) and stroke volume were higher in O and Y after 3 wk with further increases after 9 wk of training (P < 0.05). Maximal arterial-venous oxygen difference (a-vO(2 diff)) was higher at weeks 3 and 6 and posttraining compared with pretraining in O and Y (P < 0.05). In O, approximately 69% of the increase in Vo(2 max) from pre- to posttraining was explained by an increased Q(max) with the remaining approximately 31% explained by a widened a-vO(2 diff). This proportion of Q and a-vO(2 diff) contributions to the increase in Vo(2 max) was consistent throughout testing in O. In Y, 56% of the pre- to posttraining increase in Vo(2 max) was attributed to a greater Q(max) and 44% to a widened a-vO(2 diff). Early adaptations (first 3 wk) mainly relied on a widened maximal a-vO(2 diff) (approximately 66%) whereas further increases in Vo(2 max) were exclusively explained by a greater Q(max). In conclusion, with short-term training O and Y significantly increased their Vo(2 max); however, the proportion of Vo(2 max) increase explained by Q(max) and maximal a-vO(2 diff) throughout training showed a different pattern by age group.
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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".