The impact of preconditioning exercise on the vascular response to an oral glucose challenge
Bibliographic record
Abstract
Exercise elicits direct benefits to insulin sensitivity but may also indirectly improve glucose uptake by hemodynamic conditioning of the vasculature. The purpose of this study was to examine the modifying effect of 3 different types of exercise on the vascular response to an oral glucose challenge. Twenty healthy adults (9 women, 11 men; aged 23 ± 3 years) completed a standard oral glucose tolerance test (OGTT) at rest, as well as 1.5 hours after moderate continuous cycling exercise (30 min; 65% peak oxygen consumption), high-intensity interval cycling exercise (10 × 1 min at 90% peak heart rate), and lower-load higher-repetition resistance exercise (25–35 repetitions/set, 3 sets). Brachial and superficial femoral artery blood flow, conductance, and oscillatory shear index were measured throughout the OGTT. Regardless of rested state or exercise preconditioning, the OGTT induced reductions in brachial artery blood flow and conductance (p < 0.001), and transient increases in brachial and superficial femoral artery oscillatory shear index and retrograde blood flow (p < 0.01). Continuous cycling and resistance exercise were followed with a small degree of protection against prolonged periods of oscillatory flow. Our findings imply transient peripheral vasoconstriction and decreased limb blood flow during a standard OGTT, for which prior exercise was unable to prevent in healthy adults. Novelty: We investigated the impact of continuous, interval, and resistance exercise on the hemodynamic response to an OGTT. Our findings suggest decreased upper-limb blood flow during an OGTT is not prevented by prior exercise in healthy adults.
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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 | 0.000 |
| 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".