Attenuation of Smooth Muscle Cell Phenotypic Switching by Angiotensin 1-7 Protects against Thoracic Aortic Aneurysm
Bibliographic record
Abstract
Thoracic aortic aneurysm (TAA) involves extracellular matrix (ECM) remodeling of the aortic wall, leading to reduced biomechanical support with risk of aortic dissection and rupture. Activation of the renin-angiotensin system, and resultant angiotensin (Ang) II synthesis, is critically involved in the onset and progression of TAA. The current study investigated the effects of angiotensin (Ang) 1-7 on a murine model of TAA. Male 8-10-week-old ApoEKO mice were infused with Ang II (1.44 mg/kg/day) and treated with Ang 1-7 (0.576 mg/kg/day). ApoEKO mice developed advanced TAA in response to four weeks of Ang II infusion. Echocardiographic and histological analyses demonstrated increased aortic dilatation, excessive structural remodelling, perivascular fibrosis, and inflammation in the thoracic aorta. Ang 1-7 infusion led to attenuation of pathological phenotypic alterations associated with Ang II-induced TAA. Smooth muscle cells (SMCs) isolated from adult murine thoracic aorta exhibited excessive mitochondrial fission, oxidative stress, and hyperproliferation in response to Ang II. Treatment with Ang 1-7 resulted in inhibition of mitochondrial fragmentation, ROS generation, and hyperproliferation. Gene expression profiling used for characterization of the contractile and synthetic phenotypes of thoracic aortic SMCs revealed preservation of the contractile phenotype with Ang 1-7 treatment. In conclusion, Ang 1-7 prevented Ang II-induced vascular remodeling and the development of TAA. Enhancing Ang 1-7 actions may provide a novel therapeutic strategy to prevent or delay the progression of TAA.
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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 | 0.000 |
| 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) | 0.001 | 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".