High-Intensity Endurance Training Results in Faster Vessel-Specific Rate of Vasorelaxation in Type 1 Diabetic Rats
Bibliographic record
Abstract
This study examined the effects of 6 weeks of moderate- (MD) and high-intensity endurance training (HD) and resistance training (RD) on the vasorelaxation responsiveness of the aorta, iliac, and femoral vessels in type 1 diabetic (D) rats. Vasorelaxation to acetylcholine was modeled as a mono-exponential function. A potential mediator of vasorelaxation, endothelial nitric oxide synthase (e-NOS) was determined by Western blots. Vessel lumen-to-wall ratios were calculated from H&E stains. The vasorelaxation time-constant (τ) (s) was smaller in control (C) (7.2 ± 3.7) compared to D (9.1 ± 4.4) and it was smaller in HD (5.4 ± 1.5) compared to C, D, RD (8.3 ± 3.7) and MD (8.7 ± 3.8) (p<0.05). The rate of vasorelaxation (% · s(-1)) was larger in HD (2.7 ± 1.2) compared to C (2.0 ± 1.2), D (2.0 ± 1.5), RD (2.0 ± 1.0), and MD (2.0 ± 1.2) (p<0.05). τ vasorelaxation was smaller in the femoral (6.9 ± 3.7) and iliac (6.9 ± 4.7) than the aorta (9.0 ± 5.0) (p<0.05). The rate of vasorelaxation was progressively larger from the femoral (3.1 ± 1.4) to the iliac (2.0 ± 0.9) and to the aorta (1.3 ± 0.5) (p<0.05). e-NOS content (% of positive control) was greater in HD (104 ± 90) compared to C (71 ± 64), D (85 ± 65), RD (69 ± 43), and MD (76 ± 44) (p<0.05). e-NOS normalized to lumen-to-wall ratio (% · mm(-1)) was larger in the femoral (11.7 ± 11.1) compared to the aorta (3.2 ± 1.9) (p<0.05). Although vasorelaxation responses were vessel-specific, high-intensity endurance training was the most effective exercise modality in restoring the diabetes-related loss of vascular responsiveness. Changes in the vasoresponsiveness seem to be endothelium-dependent as evidenced by the greater e-NOS content in HD and the greater normalized e-NOS content in the smaller vessels.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".