Gene transfer of endothelial NO-synthase restores migratory capacity of endothelial progenitor cells from patients with coronary artery diseases
Bibliographic record
Abstract
Autologous endothelial progenitor cells (EPCs) have been used extensively in the development of cell-based therapy for acute MI. However, EPCs isolated from patients with CAD and/or CAD risk factors have reduced regenerative activity compared to cells from healthy subjects. As in endothelial cells, endothelial NO synthase (eNOS) expression and subsequent NO production are believed to be critical determinants of EPC function. Recently, the ability of EPCs to migrate in vitro in response to chemotactic stimuli has been shown to predict their regenerative capacity in clinical studies. Therefore, we hypothesized that the regenerative function of EPCs from patients with or at high risk for CAD will be enhanced by overexpression of eNOS, as assessed by migratory capacity. Methods: EPCs were isolated from the blood of human subjects with CAD risk factors (>15% Framingham risk score; FRS) (± CAD) by Ficoll gradient separation and differential culture. Following 3 days in culture, cells were transduced using lentivirus vectors containing either eNOS or GFP (sham) at an MOI of 3. The cells were cultured for an additional 5 days before being used in functional assays. Cell migration and chemotaxis in response to VEGF (50 ng/mL) and SDF-1 (100 ng/mL) were assessed using a modified Boyden Chamber assay. Results: Transduction at an MOI of 3 led to a ~90-100-fold increase in eNOS mRNA expression and a 5-6 fold increase in eNOS protein expression, as assessed by qRT-PCR and Western Blotting. Moreover, there was a significant improvement in the migration of EPCs following eNOS transduction compared to sham-transduced EPCs in response to both VEGF (44.3 ± 8.4 vs. 31.1 ± 4.6 cells/high power field; n=10, p < 0.05) and SDF-1 (51.9 ± 11.1 vs. 34.5 ± 3.3 cells/HPF; n=10, p < 0.05). Conclusions: These data show that the reduced migration capacity of EPCs isolated from patients with CAD and/or CAD risk factors can be significantly improved through eNOS overexpression in these cells. Thus, eNOS transduction of autologous EPCs may enhance their ability to restore myocardial perfusion and function following acute MI. We intend to further explore the regenerative potential of eNOS-transduced EPCs using various in vitro and in vivo models.
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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".