Paracrine Engineering of Human Cardiac Stem Cells With Insulin‐Like Growth Factor 1 Enhances Myocardial Repair
Bibliographic record
Abstract
BACKGROUND: Insulin-like growth factor 1 (IGF-1) activates prosurvival pathways and improves postischemic cardiac function, but this key cytokine is not robustly expressed by cultured human cardiac stem cells. We explored the influence of an enhanced IGF-1 paracrine signature on explant-derived cardiac stem cell-mediated cardiac repair. METHODS AND RESULTS: Receptor profiling demonstrated that IGF-1 receptor expression was increased in the infarct border zones of experimentally infarcted mice by 1 week after myocardial infarction. Human explant-derived cells underwent somatic gene transfer to overexpress human IGF-1 or the green fluorescent protein reporter alone. After culture in hypoxic reduced-serum media, overexpression of IGF-1 enhanced proliferation and expression of prosurvival transcripts and prosurvival proteins and decreased expression of apoptotic markers in both explant-derived cells and cocultured neonatal rat ventricular cardiomyocytes. Transplant of explant-derived cells genetically engineered to overexpress IGF-1 into immunodeficient mice 1 week after infarction boosted IGF-1 content within infarcted tissue and long-term engraftment of transplanted cells while reducing apoptosis and long-term myocardial scarring. CONCLUSIONS: Paracrine engineering of explant-derived cells to overexpress IGF-1 provided a targeted means of improving cardiac stem cell-mediated repair by enhancing the long-term survival of transplanted cells and surrounding myocardium.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".