Cardiomyocyte Induction and Regeneration for Myocardial Infarction Treatment: Cell Sources and Administration Strategies
Bibliographic record
Abstract
Occlusion of coronary artery and subsequent damage or death of myocardium can lead to myocardial infarction (MI) and even heart failure-one of the leading causes of deaths world wide. Notably, myocardium has extremely limited regeneration potential due to the loss or death of cardiomyocytes (i.e., the cells of which the myocardium is comprised) upon MI. A variety of stem cells and stem cell-derived cardiovascular cells, in situ cardiac fibroblasts and endogenous proliferative epicardium, have been exploited to provide renewable cellular sources to treat injured myocardium. Also, different strategies, including direct injection of cell suspensions, bioactive molecules, or cell-incorporated biomaterials, and implantation of artificial cardiac scaffolds (e.g., cell sheets and cardiac patches), have been developed to deliver renewable cells and/or bioactive molecules to the MI site for the myocardium regeneration. This article briefly surveys cell sources and delivery strategies, along with biomaterials and their processing techniques, developed for MI treatment. Key issues and challenges, as well as recommendations for future research, are also discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".