An optimal non-viral gene transfer method for genetically modifying porcine bone marrow-derived endothelial progenitor cells for experimental therapeutics
Bibliographic record
Abstract
No currently available treatment is able to generate new contractile tissue or significantly improve cardiac function after myocardial infarction (MI), a leading cause of morbidity and mortality worldwide. Although gene transfer-enhanced endothelial progenitor cells (GTE-EPCs) show effectiveness in MI treatment in small animal models, no clinical trials using GTE-EPCs have been documented. Before the introduction of GTE-EPCs into human trials, gene-transfer-mediated augmentation of EPC function in animal models that reflect the human MI scenario should be tested. In this regard, a porcine model is the best choice since pigs have cardiac size, hemodynamics and coronary anatomy similar to that of humans. To examine GTE-EPC therapeutic efficacy in pig MI models, an efficient method for gene transfer into pig EPCs is required, which however, has been poorly documented. Pig bone marrow mononuclear cells were isolated and cultured in EGM-2 medium to obtain bone marrow-derived EPCs (BM-EPCs) that were characterized by immunostaining and the tube formation assay. Gene transfer was optimized in 6-well plates using a GFP and a VEGF plasmid, and scaled up in T75 flasks. Gene transfer efficiency was determined by fluorescence microscopy and flow cytometry. VEGF levels were measured by ELISA. Cell proliferation was assayed by the CCK-8 kit. (1) BM-EPCs expressed VEGFR2 and eNOS but not CD45 protein, and formed tube structures on Matrigel; (2) several chemical compounds were explored with the highest transfection efficiency of 41.4% ± 5.8% achieved using Lipofectamine 3000; (3) the VEGF level in culture medium after VEGF transfection was 378 ± 48 ng/10 6 cells; and (4) BM-EPCs overexpressing VEGF had significantly enhanced proliferation than GFP-transfected EPCs. A simple, easy and cheap method that can be applied to produce a large number of genetically-modified BM-EPCs was established, which will facilitate the study of GTE-EPC therapeutic efficacy in pig MI model.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".