AAV9.I-1c Delivered via Direct Coronary Infusion in a Porcine Model of Heart Failure Improves Contractility and Mitigates Adverse Remodeling
Bibliographic record
Abstract
BACKGROUND: Heart failure is characterized by impaired function and disturbed Ca2+ homeostasis. Transgenic increases in inhibitor-1 activity have been shown to improve Ca2 cycling and preserve cardiac performance in the failing heart. The aim of this study was to evaluate the effect of activating the inhibitor (I-1c) of protein phosphatase 1 (I-1) through gene transfer on cardiac function in a porcine model of heart failure induced by myocardial infarction. METHODS AND RESULTS: Myocardial infarction was created by a percutaneous, permanent left anterior descending artery occlusion in Yorkshire Landrace swine (n=16). One month after myocardial infarction, pigs underwent intracoronary delivery of either recombinant adeno-associated virus type 9 carrying I-1c (n=8) or saline (n=6) as control. One month after myocardial infarction was created, animals exhibited severe heart failure demonstrated by decreased ejection fraction (46.4±7.0% versus sham 69.7±8.5%) and impaired (dP/dt)max and (dP/dt)min. Intracoronary injection of AAV9.I-1c prevented further deterioration of cardiac function and led to a decrease in scar size. CONCLUSIONS: In this preclinical model of heart failure, overexpression of I-1c by intracoronary in vivo gene transfer preserved cardiac function and reduced the scar size.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".