Enhanced Inhibition of Neointimal Hyperplasia by Genetically Engineered Endothelial Progenitor Cells
Bibliographic record
Abstract
BACKGROUND: Circulating endothelial progenitor cells (EPCs) have been reported previously. In this study, we examined the hypothesis that overexpression of vasculoprotective gene endothelial nitric oxide synthase (eNOS) and heme oxygenase-1 (HO-1) in EPCs enhances their ability to inhibit neointimal hyperplasia. METHODS AND RESULTS: EPCs were isolated from rabbit peripheral blood, expanded in culture, and transduced with pseudotyped retroviral vectors expressing human eNOS (eNOS-EPCs), HO-1 (HO-1-EPCs), or green fluorescent protein (GFP-EPCs). Transduction efficiency of EPCs ex vivo was >90%. Four groups of rabbits (n=5 to 6 per group) were subjected to balloon angioplasty of the common carotid artery. Immediately after injury, approximately 5x10(6) autologous eNOS-EPCs or HO-1-EPCs were transplanted into the injured vessel. Control animals received an equivalent number of GFP-EPCs or Ringer's saline. Two weeks after transplantation, eNOS and HO-1 transgene transcripts and proteins were detected in the transduced rabbit vessels. Endothelialization was enhanced in the EPC-transplanted vessels independently of gene transfer. Neointimal thickening was significantly reduced in the GFP-EPC-treated vessels relative to the saline control. Neointima size was further reduced in vessels treated with eNOS-EPCs. Surprisingly, no additional reduction was seen in vessels treated with HO-1-EPCs relative to GFP-EPCs. Thrombosis occurred in approximately 50% of the saline-treated vessels but was virtually absent in all EPC-transplanted vessels. CONCLUSIONS: We conclude that transplantation of autologous EPCs overexpressing eNOS in injured vessels enhances the vasculoprotective properties of the reconstituted endothelium, leading to inhibition of neointimal hyperplasia. This cell-based gene therapy strategy may be useful in treatment of vascular disease.
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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".