Abstract 43: A Functional Angiotensin Type 1a Receptor Is Required for Aldosterone to Induce Small Artery Endothelial Dysfunction, Inflammation and Oxidative Stress
Bibliographic record
Abstract
Background: Aldosterone induces hypertension, endothelial dysfunction, vascular inflammation and oxidative stress. Recent in vitro studies suggest that there may be cross-talk between angiotensin II and aldosterone pathways. We hypothesized that in vivo vascular effects of aldosterone require a functional angiotensin II type 1a receptor (Agtr1a). Design and methods: Eight to 10-week old male agtr1a knockout ( agtr1a -/- ) and wild-type mice were implanted with a dummy pump or infused with aldosterone (600 μg/kg/d, s.c.) for 14 days while receiving 1% saline in the drinking water (n=8-10). Systolic blood pressure (SBP) was measured by telemetry. Endothelial function, and reactive oxygen species (ROS) production were assessed in mesenteric arteries using pressurized myography and dihydroethidium staining, respectively. Levels of collagen by Sirius red staining and fibronectin, VCAM-1, and MCP-1 by immunofluorescence were determined in aortic sections. Results: Aldosterone-induced higher levels of SBP in agtr1a -/- compared to wild-type mice (about 15 mmHg, P <0.01). Maximal vasodilatory responses to acetylcholine in mesenteric small arteries were similar in agtr1a -/- and wild-type mice. Aldosterone reduced maximal vasodilatory responses to acetylcholine in wild-type mice by 48% ( P <0.05) whereas there was no effect in agtr1a -/- mice. Aldosterone increased ROS production 2-fold in mesenteric arteries of wild-type mice ( P <0.05) whereas it had no effect in agtr1a -/- mice. Aldosterone increased VCAM-1 (1.8-fold, P <0.05), MCP-1 (2.7-fold, P <0.05), fibronectin (3-fold, P <0.01) and collagen (3.9-fold, P <0.05) in aorta of wild-type but not in agtr1a -/- mice. Conclusion: Aldosterone requires functional Agtr1a to induce small artery endothelial dysfunction and vascular oxidative stress, inflammation and fibrosis.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".