Left ventricular pressure‐loading improves pressure‐induced right ventricular remodeling by redistributing mechanical load and reducing mechanosignaling
Bibliographic record
Abstract
Right ventricular (RV) function under pressure overload (PO) is critical in congenital heart disease outcomes. While moderate left ventricular (LV) pressure-loading has been shown to benefit RV function, the mechanisms and optimal degree of loading remain unclear. This study investigated whether increasing LV afterload could enhance RV function, remodeling, and molecular signaling. Using computational modeling and an in vivo "double-banding" (DB) approach in Sprague-Dawley rats-constricting both the pulmonary artery (PA) and transverse aorta-the effects of LV loading were assessed. Modeling suggested that LV pressure-loading improves RV contractility by homogenizing RV load. In vivo, DB rats exhibited higher tricuspid annular plane systolic excursion (TAPSE) compared to those with only pulmonary artery banding (PAB). Hemodynamic analysis showed reduced end-diastolic pressure (EDP) and increased end-diastolic pressure-volume relationship (EDPVR) in DB rats. Histological examination revealed less RV fibrosis in DB rats with moderate LV loading (DBmod) than in those with mild loading (DBmild) or PAB. Molecular studies indicated that markers of fibrosis and maladaptive signaling were elevated in PAB RVs but normalized or downregulated in DBmod RVs. These findings suggest that moderate LV pressure-loading during RV-PO improves RV remodeling and function, providing mechanistic insights and potential therapeutic strategies for congenital heart disease.
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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 | 0.000 |
| 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".