Prior Heavy Exercise Improves VO2 Kinetics and Muscle Oxygenation During Moderate Exercise in Young Adults
Bibliographic record
Abstract
0164 PURPOSE: To examine the effect of prior heavy-intensity exercise on the adaptation of pulmonary O2 uptake (ôVO2) during moderate-intensity exercise in young adults with fast and slow VO2 kinetics. METHODS: Healthy young adults were divided into two groups: ôVO2 < 30s (FK; n = 6) and ôVO2 > 30s (SK; n = 6). Each subject performed 4 repetitions of a MOD1-HVY-MOD2 protocol from 20W to work rates corresponding to 80% of the estimated lactate threshold (θL) (MOD1; MOD2), and 50% of the difference between θL and VO2peak (HVY). Each transition lasted 6 min and each was separated by 6 min cycling at 20 W. VO2 was measured breath-by-breath and heart rate (HR) was measured beat-by-beat. The change in total (HbTOT), Oxy-(HbO2), and Deoxy-hemoglobin (HHb) concentrations were monitored continuously by near-infrared spectroscopy (Hamamatsu NIRO 300). Phase II VO2 (ôVO2) kinetics, and HHb (ôHHb) kinetics were modelled using a mono-exponential equation and non-linear regression techniques. RESULTS: τVO2 decreased (P<0.05) in Mod2 in both FK (Mod1, 26±5 s, Mod2, 20±5 s; P<0.05) and SK (Mod1, 45±11 s, Mod2, 30±8 s, P<0.05) with the decrease being greater in subjects having a greater τVO2 in Mod1. Baseline HR, HbTOT and Hb O2 were elevated (P<0.05) in Mod2 compared to Mod1. The delay prior to an increase in HHb(TD HHb) was decreased in Mod2 (FK, 12±4 s; SK, 9±3 s) compared to Mod2 (FK, 19±4 s; SK, 15±3 s) but τHHb was not changed (FK: Mod1, 13±8 s, Mod2, 10±2 (P>0.05); SK: Mod1, 19±12 s; Mod2, 27±12 (P = 0.065)). CONCLUSION: In young adults, a greater “speeding” of VO2 kinetics was seen following HVY in those subjects having a greater τVO2 in Mod1. The faster adaptation may be related to both an improved muscle perfusion (i.e. higher HR, HbTOT and HbO 2 prior to Mod2) and to an accelerated rate of O2 utilization relative to perfusion (i.e. shorter HHb TD). Supported by NSERC, Canada
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) | 0.001 | 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) | 0.002 | 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".