Gene therapy strategy to enhance survival and function of endothelial progenitor cells (EPC) in the infarct environment
Bibliographic record
Abstract
Endothelial progenitor cells (EPC) are endothelial cell precursors originating in the hematopoietic compartment of the bone marrow, and are thought to be a useful substrate for clinical neovascularization in patients with coronary or peripheral ischemic artery disease. However the prevailing pro‐oxidant and pro‐inflammatory milieu of the infarct environment (IE) markedly reduces EPC engraftment, survival and function after transplantation or mobilization with cytokines. As a strategy to enhance the viability of EPC in the cytotoxic IE, we genetically modified human EPC with retroviral vectors (MSCV) expressing heme oxygenase‐1 (HO‐1) and Akt and exposed the cells to a simulated IE of hypoxia (1% O 2 ), oxidative stress (300 μM H 2 O 2 ) and inflammatory cytokine stimulation (25 ng/ml TNF‐α). EPC's were transduced with 10 MOI of MSCV‐HO‐1 and 10 MOI of MSCV‐Akt and exposed to IE for 24 hr. HO‐1 and Akt co‐expression markedly decreased reactive oxygen species generation and significantly reduced the number of annexin V‐ and propidium iodide‐positive cells, leading to enhanced cell viability. Compared to GFP‐transduced control cells, adhesion of EPC to extracellular matrix substrates was enhanced in HO‐1/Akt modified cells in the IE. We conclude that genetic modification of EPC with HO‐1 and Akt markedly enhances their survival and function in the IE and may facilitate their role in neovascularization and healing of ischemic and infarcted myocardium. Supported by grants from the HSFO to LG Melo and CA Ward .
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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".