Using Acellular Bioactive Extracellular Matrix Scaffolds to Enhance Endogenous Cardiac Repair
Bibliographic record
Abstract
An inability to recover lost cardiac muscle following acute ischemic injury remains the biggest shortcoming of current therapies to prevent heart failure. As compared to standard medical and surgical treatments, tissue engineering strategies offer the promise of improved heart function by inducing regeneration of functional heart muscle. Tissue engineering approaches that use stem cells and genetic manipulation have shown promise in preclinical studies but have also been challenged by numerous critical barriers preventing effective clinical translational. We believe that surgical intervention using acellular bioactive ECM scaffolds may yield similar therapeutic benefits with minimal translational hurdles. In this review, we outline the limitations of cellular-based tissue engineering strategies and the advantages of using acellular biomaterials with bioinductive properties. We highlight key anatomic targets enriched with cellular niches that can be uniquely activated using bioactive scaffold therapy. Finally, we review the evolving cardiovascular tissue engineering landscape and provide critical insights into the potential therapeutic benefits of acellular scaffold therapy.
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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 | 0.001 | 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".