Kinetics of V<scp>o</scp><sub>2</sub> and femoral artery blood flow during heavy-intensity, knee-extension exercise
Bibliographic record
Abstract
It has been suggested that, during heavy-intensity exercise, O(2) delivery may limit oxygen uptake (.VO2) kinetics; however, there are limited data regarding the relationship of blood flow and .VO2 kinetics for heavy-intensity exercise. The purpose was to determine the exercise on-transient time course of femoral artery blood flow (Q(leg)) in relation to .VO2 during heavy-intensity, single-leg, knee-extension exercise. Five young subjects performed five to eight repeats of heavy-intensity exercise with measures of breath-by-breath pulmonary .VO2 and Doppler ultrasound femoral artery mean blood velocity and vessel diameter. The phase 2 time frame for .VO2 and Q(leg) was isolated and fit with a monoexponent to characterize the amplitude and time course of the responses. Amplitude of the phase 3 response was also determined. The phase 2 time constant for .VO2 of 29.0 s and time constant for Q(leg) of 24.5 s were not different. The change (Delta) in .VO2 response to the end of phase 2 of 0.317 l/min was accompanied by a DeltaQ(leg) of 2.35 l/min, giving a DeltaQ(leg)-to-Delta.VO2 ratio of 7.4. A slow-component .VO2 of 0.098 l/min was accompanied by a further Q(leg) increase of 0.72 l/min (DeltaQ(leg)-to-Delta.VO2 ratio = 7.3). Thus the time course of Q(leg) was similar to that of muscle .VO2 (as measured by the phase 2 .VO2 kinetics), and throughout the on-transient the amplitude of the Q(leg) increase achieved (or exceeded) the Q(leg)-to-.VO2 ratio steady-state relationship (ratio approximately 4.9). Additionally, the .VO2 slow component was accompanied by a relatively large rise in Q(leg), with the increased O(2) delivery meeting the increased Vo(2). Thus, in heavy-intensity, single-leg, knee-extension exercise, the amplitude and kinetics of blood flow to the exercising limb appear to be closely linked to the .VO2 kinetics.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".