Role of aldosterone in angiotensin II-induced cardiac and aortic inflammation, fibrosis, and hypertrophy
Bibliographic record
Abstract
Activation of the renin-angiotensin-aldosterone system is associated with increased extracellular matrix and inflammatory markers in the cardiovascular system. We evaluated the effects of aldosterone antagonism on cardiovascular structure, collagen deposition, and expression of inflammatory markers in 2-week angiotensin (Ang) II-infused rats (120 ng.kg-1.min-1, s.c.)+/-spironolactone or hydralazine (25 mg.kg-1.d-1). Aortic and cardiac collagen density was evaluated with Sirius red staining. NFkappaB and AP-1 were measured by a electrophoretic mobility shift assay, and ED-1 (macrophage marker) and vascular cell adhesion molecule-1 (VCAM-1) were measured by immunohistochemistry. Ang II increased blood pressure (176+/-2 mmHg vs. 115+/-1 mmHg in controls, p<0.01), which was attenuated by spironolactone (147+/-4 mmHg, p<0.01) and prevented by hydralazine (124+/-2 mmHg, p<0.01). Ang II enhanced left ventricular interstitial collagen type I/III deposition (4.1%+/-0.1% vs. 3.1%+/-0.2%, p<0.05), and this was attenuated by spironolactone but not hydralazine. Ang II-induced cardiac perivascular fibrosis was prevented by spironolactone and hydralazine. Ang II significantly increased cardiac AP-1 activity and ED-1 expression, which was prevented by spironolactone only. Ang II-enhanced NFkappaB activity, and VCAM-1 expression was reduced by spironolactone and hydralazine, whereas aortic hypertrophy was prevented by spironolactone and slightly reduced by hydralazine. In conclusion, blockade of mineralocorticoid receptors with spironolactone inhibited Ang II-induced aortic hypertrophy, cardiac transcription factor activation, upregulation of downstream inflammatory markers, and collagen deposition, thus preventing Ang II-induced cardiovascular damage.
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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".