Bcl-2 Engineered MSCs Inhibited Apoptosis and Improved Heart Function
Bibliographic record
Abstract
Engraftment of mesenchymal stem cells (MSCs) derived from adult bone marrow has been proposed as a potential therapeutic approach for postinfarction left ventricular dysfunction. However, limited cell viability after transplantation into the myocardium has restricted its regenerative capacity. In this study, we genetically modified MSCs with an antiapoptotic Bcl-2 gene and evaluated cell survival, engraftment, revascularization, and functional improvement in a rat left anterior descending ligation model via intracardiac injection. Rat MSCs were manipulated to overexpress the Bcl-2 gene. In vitro, the antiapoptotic and paracrine effects were assessed under hypoxic conditions. In vivo, the Bcl-2 gene-modified MSCs (Bcl-2-MSCs) were injected after myocardial infarction. The surviving cells were tracked after transplantation. Capillary density was quantified after 3 weeks. The left ventricular function was evaluated by pressure-volume loops. The Bcl-2 gene protected MSCs against apoptosis. In vitro, Bcl-2 overexpression reduced MSC apoptosis by 32% and enhanced vascular endothelial growth factor secretion by more than 60% under hypoxic conditions. Transplantation with Bcl-2-MSCs increased 2.2-fold, 1.9-fold, and 1.2-fold of the cellular survival at 4 days, 3 weeks, and 6 weeks, respectively, compared with the vector-MSC group. Capillary density in the infarct border zone was 15% higher in Bcl-2-MSC transplanted animals than in vector-MSC treated animals. Furthermore, Bcl-2-MSC transplanted animals had 17% smaller infarct size than vector-MSC treated animals and exhibited functional recovery remarkably. Our current findings support the premise that transplantation of antiapoptotic gene-modified MSCs may have values for mediating substantial functional recovery after acute myocardial infarction.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".