Oxygen uptake kinetics for moderate exercise are speeded in older humans by prior heavy exercise
Bibliographic record
Abstract
This study examined the effect of heavy-intensity warm-up exercise on O(2) uptake (VO(2)) kinetics at the onset of moderate-intensity (80% ventilation threshold), constant-work rate exercise in eight older (65 +/- 2 yr) and seven younger adults (26 +/- 1 yr). Step increases in work rate from loadless cycling to moderate exercise (Mod(1)), heavy exercise, and moderate exercise (Mod(2)) were performed. Each exercise bout was 6 min in duration and separated by 6 min of loadless cycling. VO(2) kinetics were modeled from the onset of exercise by use of a two-component exponential model. Heart rate (HR) kinetics were modeled from the onset of exercise using a single exponential model. During Mod(1), the time constant (tau) for the predominant rise in VO(2) (tau VO(2)) was slower (P < 0.05) in the older adults (50 +/- 10 s) than in young adults (19 +/- 5 s). The older adults demonstrated a speeding (P < 0.05) of VO(2) kinetics when moderate-intensity exercise (Mod(2)) was preceded by high-intensity warm-up exercise (tau VO(2), 27 +/- 3 s), whereas young adults showed no speeding of VO(2) kinetics (tau VO(2), 17 +/- 3 s). In the older and younger adults, baseline HR preceding Mod(2) was elevated compared with Mod(1), but the tau for HR kinetics was slowed (P < 0.05) in Mod(2) only for the older adults. Prior heavy-intensity exercise in old, but not young, adults speeded VO(2) kinetics during Mod(2). Despite slowed HR kinetics in Mod(2) in the older adults, an elevated baseline HR before the onset of Mod(2) may have led to sufficient muscle perfusion and O(2) delivery. These results suggest that, when muscle blood flow and O(2) delivery are adequate, muscle O(2) consumption in both old and young adults is limited by intracellular processes within the exercising muscle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".