Adverse Biventricular Remodeling in Isolated Right Ventricular Hypertension Is Mediated by Increased Transforming Growth Factor–β1 Signaling and Is Abrogated by Angiotensin Receptor Blockade
Bibliographic record
Abstract
The pressure-loaded right ventricle (RV) adversely affects left ventricular (LV) function. We recently found that these ventricular-ventricular interactions lead to LV myocardial fibrosis through transforming growth factor-β1 (TGF-β1) signaling. We investigated the mechanisms mediating biventricular fibrosis in RV afterload and their potential modification by angiotensin receptor blockade. An adjustable pulmonary artery band (PAB) was placed in rabbits. In sham-operated control rabbits, the band was left uninflated (n = 6). In the RV afterload group, the PAB was sequentially inflated to generate systemic RV pressure at 28 days (n = 8). In a third group, the PAB was inflated to systemic levels, and the angiotensin receptor blocker losartan was added (n = 6). Five weeks after surgery, the animals were killed for assessments of biventricular hypertrophy, fibrosis, apoptosis, and the components of their signaling pathways. PAB animals developed biventricular hypertrophy, fibrosis, and apoptosis, versus sham rabbits, in which these conditions were decreased with losartan. RV and LV TGF-β1, connective tissue growth factor (CTGF) (CCN2), endothelin-1 (ET-1), endothelin receptor B, and matrix metalloproteinase 2/9 mRNA levels were increased in PAB animals versus sham animals, and decreased with losartan. Given the marked biventricular CTGF up-regulation in PAB and down-regulation with losartan, we investigated CTGF signaling. RV and LV Smad 2/3/4 protein levels and LV RhoA mRNA levels were increased with PAB and reduced with losartan. In conclusion, isolated RV afterload induces biventricular fibrosis and apoptosis, which are reduced by angiotensin receptor blockade. Adverse ventricular-ventricular interactions induced by isolated RV afterload appear to be mediated through TGF-β1-CTGF and ET-1 pathways.
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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".