Nitric oxide‐dependent regulation of coronary vascular resistance in hypertension
Bibliographic record
Abstract
Hypertension is associated with impaired endothelium dependent relaxations in many vascular beds. Evidence from the coronary vasculature offers conflicting results. The current investigation examined the role of NO in regulating coronary vascular resistance (CVR) in spontaneously hypertensive rats (SHR) and their normotensive counterparts (WKY). Rats were anesthetized, the hearts were removed and the aorta was cannulated to allow for retrograde coronary perfusion using a constant flow Langendorff set‐up. Flow was assigned based on heart weight which was estimated from body weight. SHR had a greater baseline CVR than the WKY (6.72±0.34 vs 4.97±0.62 mmHg/ml/min, p<0.05). Following ET‐1 administration SHR had a greater resistance (9.82±0.75 vs 6.87±0.96 mmHg/ml/min, p<0.05) although the absolute change was not different. There were no differences in maximal reduction in CVR to bradykinin (BK) or sensitivity to BK. Treatment with LNAME caused an increase in resistance in both groups although the change in resistance was not different between the SHR and WKY (3.46±0.41 vs 3.02±0.69 p>0.05). LNAME completely abolished the BK induced reduction in CVR in both the SHR and WKY; the response to sodium nitroprusside was unchanged. Thus, the response to BK is NO dependent in both SHR and WKY. The CVR is elevated in the SHR and inhibition of eNOS increases CVR to a similar extent in both strains. Funded by NSERC & HSFO
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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) | 0.000 | 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 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".