Abstract 10751: Pericardial Injection of Micronized Matrix Biomaterial Improves Post-Infarct Cardiac Function and Modulates Fibroblast Activity to Enhance Repair
Bibliographic record
Abstract
Introduction: Injection of micronized biomaterials into the pericardial space leverages bioinductive properties to enhance post-infarct cardiac repair. This less invasive, potentially bedside, approach enables early intervention. Micronized porcine small intestinal submucosal extracellular matrix (SIS-ECM) contains fibroblast growth factor 2 (FGF2) which reduce fibrosis and increase vasculogenesis. Hypothesis: Pericardial delivery of micronized SIS-ECM improves post-infarct cardiac function. It promotes a proangiogenic and antifibrotic fibroblast phenotype. Methods: Mice received coronary ligation (infarct) through an undisrupted pericardium followed by pericardial delivery of micronized SIS-ECM or saline control. Pressure-volume loops were at 28 days. Myocardial isolectin stain assessed small vessel density on confocal microscopy. Mouse 3T3 cell line fibroblasts in 3D collagen matrices were exposed to biomaterial-conditioned media or media control. Multiplex analyzed paracrine activity. Collagen gel contraction and MMP2 production assessed profibrotic phenotype. FGF2 inhibitor elucidated mechanism. Results: Mice receiving micronized SIS-ECM had lower ventricular stiffness (0.23±0.03 vs 0.39±0.05 mmHg/uL; p=0.01), higher ejection fraction (34.7±2.5 vs 26.9±2.8%; p<0.05) and higher stroke work (1510±138 vs 1066±152 μL/mmHg; p=0.04). The SIS-ECM group had higher normalized border zone isolectin mean fluorescence (0.82±0.04 vs 0.58±0.06; p=0.01). Micronized SIS-ECM attenuated collagen gel contraction (26±6 vs 56±5%; p=0.01) and MMP2 release (66±2 vs 83±3 ng/mL; p<0.01). Micronized SIS-ECM increased fibroblast VEGF production (904±79 vs 628±25; pg/mL). FGF2 inhibitor negated biomaterial effects, increasing gel contraction (27.3±5.3 vs 11.0±0.5%; p=0.04; inhibitor vs no inhibitor) and MMP-2 release (141±8 vs 100±6 ng/mL; p=0.02). Conclusions: Pericardial injection of micronized SIS-ECM attenuates profibrotic fibroblast activity, increases release of angiogenic VEGF protein, increases vasculogenesis on isolectin staining, and preserves post-infarct cardiac function. This less invasive strategy facilitates early intervention to attenuate maladaptive post-infarct structural remodeling.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".