Acute endurance exercise induces changes in vasorelaxation responses that are vessel-specific
Bibliographic record
Abstract
The dynamic adjustment and amplitude of the endothelium-dependent vasorelaxation of the carotid, aorta, iliac, and femoral vessels were measured in response to acute low- (LI) or high-intensity (HI) endurance exercise. Vasorelaxation to 10(-4) M ACh was evaluated in 10 control, 10 LI, and 10 HI rats. Two-millimeter sections of carotid, aorta, iliac, and femoral arteries were mounted onto a myography system. Vasorelaxation responses were modeled as a monoexponential function. The overall τ (control, 10.5 ± 6.0 s; LI, 10.4 ± 5.7 s; HI, 11.0 ± 6.9 s) and time-to-steady-state (control, 47.6 ± 24.0 s; LI, 46.2 ± 22.8 s; HI, 49.1 ± 28.3 s) was similar in LI, HI, and control (P > 0.05). The overall (average of four vessel-type) % vasorelaxation was larger in LI (73 ± 16%) and HI (73 ± 16%) than in control (66 ± 19%) (P < 0.05). The overall rate of vasorelaxation was greater in LI (1.9 ± 0.9%·s(-1)) and HI (1.9 ± 1.1%·s(-1)) compared with control (1.6 ± 0.7%·s(-1)) (P < 0.05). The vessel-specific responses (average response for the three conditions) showed that carotid displayed a slower adjustment (τ, 18.9 ± 4.4 s; time-to-steady-state, 80.4 ± 18.4 s) compared with the aorta (τ, 10.3 ± 3.8 s; time-to-steady-state, 46.3 ± 15.2 s), the iliac (τ, 6.3 ± 2.1 s; time-to-steady-state, 30.3 ± 9.0 s), and the femoral (τ, 6.0 ± 1.9 s; time-to-steady-state, 29.3 ± 8.4 s). The % vasorelaxation was larger in the carotid (82 ± 14%) than in the aorta (67 ± 16%), iliac (61 ± 13%), and femoral (71 ± 19%) (P > 0.05). The rate of vasorelaxation was carotid (1.1 ± 0.2%·s(-1)), aorta (1.5 ± 0.4%·s(-1)), iliac (2.2 ± 0.8%·s(-1)), and femoral (2.6 ± 1.0%·s(-1)). In conclusion, an acute bout of endurance exercise increased vascular responsiveness. The dynamic and percent adjustments were vessel-specific with vessel function likely determining the response.
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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 | 0.001 |
| 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".