Angiotensin Type 2 Receptor in Resistance Arteries of Type 2 Diabetic Hypertensive Patients
Bibliographic record
Abstract
The role of angiotensin type 2 receptor (AT(2)R) on vascular responses to angiotensin II in humans remains unclear. In this study we explored whether AT(2)R is expressed and functionally active on peripheral resistance arteries of hypertensive diabetic patients treated for 1 year with either the angiotensin receptor blocker valsartan or the beta-blocker atenolol. Twenty-six hypertensive type 2 diabetic patients treated with oral hypoglycemic and antihypertensive agents (not receiving angiotensin receptor blockers or beta-blockers) were randomly assigned to double-blind treatment for 1 year with valsartan or atenolol once daily added to their previous therapy in a clinical trial that we reported recently and compared with 10 normal subjects. Resistance arteries dissected from gluteal subcutaneous tissues were assessed on a pressurized myograph. Vasomotor response curves to angiotensin II (1 nmol/L to 1 micromol/L) were performed on norepinephrine precontracted vessels in the presence of valsartan (10 micromol/L) with or without the AT(2)R inhibitor PD123319 (1 micromol/L). AT(2)R expression was evaluated by confocal microscopy. After 1 year of treatment, systolic and diastolic blood pressure was controlled and comparable in the valsartan and atenolol groups. Angiotensin II evoked a significant vasodilatory response only on resistance arteries from patients treated with valsartan, effect blocked by PD123319. AT(2)R expression was 4-fold higher in small arteries of valsartan-treated patients. In conclusion, AT(2)Rs are upregulated and contribute to angiotensin II-induced vasodilation in resistance arteries of hypertensive diabetic patients treated with angiotensin type 1 receptor blockers and may mediate, in part, vascular actions of these drugs in high cardiovascular risk patients.
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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 | 0.001 |
| 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) | 0.002 | 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".