Isolation and Transplantation of Autologous Circulating Endothelial Cells Into Denuded Vessels and Prosthetic Grafts
Bibliographic record
Abstract
BACKGROUND: Blood-borne endothelial cells originating from adult bone marrow were reported previously. These cells have the properties of an endothelial progenitor cell (EPC) and can be mobilized by cytokines and recruited to sites of neovascularization, where they differentiate into mature endothelial cells. Current protocols for isolation of EPCs from peripheral blood rely on enrichment and selection of CD34+ mononuclear cells. METHODS AND RESULTS: In this report, we describe a streamlined method for the isolation and expansion of EPCs from peripheral blood and evaluate their therapeutic potential for autologous cell-based therapy of injured blood vessels and prosthetic grafts. A subset of unfractionated mononuclear cells exhibited the potential to differentiate in vitro into endothelial cells under selective growth conditions. The cells were efficiently transduced ex vivo by a retroviral vector expressing the LacZ reporter gene and could be expanded to yield sufficient numbers for therapeutic applications. Transplantation of these cells into balloon-injured carotid arteries and into bioprosthetic grafts in rabbits led to rapid endothelialization of the denuded vessels and graft segments, resulting in significant reduction in neointima deposition. CONCLUSIONS: We conclude that transplantation of EPCs may play a crucial role in reestablishing endothelial integrity in injured vessels, thereby inhibiting neointimal hyperplasia. These findings may have implications for novel and practical cell-based therapies for 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 | 0.000 |
| 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".