Abstract Thu170: Healing Hearts: The Role of Endothelial Colony–Forming Cell Exosomes in Angiogenesis and Cardiac Repair After Myocardial Infarction
Bibliographic record
Abstract
Despite improvements in therapeutics, ischemic heart disease remains a leading cause of death. Cardiac remodeling after myocardial infarction (MI), predominantly due to loss of cardiomyocytes and coronary vasculature, leads to a progressive decline in cardiac function resulting in heart failure. Cell transplantation therapy upon MI is a very promising therapeutic strategy to replace dead myocardium, reducing scarring and improving cardiac performance. The present study focused on endothelial colony–forming cell–derived exosomes (ECFC–exosomes), which are actively secreted endocytic nanovesicles (30−100 nm) that transport functional miRNAs, proteins, mRNAs, and lipids, playing a key role in paracrine intercellular communication. A novel ability of ECFC–exosomes to promote angiogenesis and cardiac tissue repair was identified. Administration of ECFCs to mice following experimental end–organ ischemia resulted in an ECFC–exosome–dependent increase in angiogenesis. ECFC–derived exosomes were taken up by endothelial cells, leading to their increased proliferation and migration, tube formation, and formation of new vessels. Administration of ECFC–exosome to a murine model of myocardial infarction prevented cardiac remodeling and heart failure. Next–generation sequencing and bioinformatics analyses identified 136 miRNAs present in ECFC−exosome cargo and factor inhibiting HIF–1α and PTEN as their potential targets in endothelial cells. Multiomics and bioinformatics analysis identified Tead1 as a potential target of ECFC–derived exosomes. Pharmacological inhibition of TEAD1 validated its role in the cardioprotective effects of EFCF–exosomes. Our findings support the view that the ECFC–exosomes represent a novel therapeutic approach to improve cardiac repair and prevent the onset of heart failure after MI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".