Angiopoietin-1-expressing adipose stem cells genetically modified with baculovirus nanocomplex: investigation in rat heart with acute infarction
Bibliographic record
Abstract
The objective of this study was to develop angiopoietin-1 (Ang1)-expressing genetically modified human adipose tissue derived stem cells (hASCs) for myocardial therapy. For this, an efficient gene delivery system using recombinant baculovirus complexed with cell penetrating transactivating transcriptional activator TAT peptide/deoxyribonucleic acid nanoparticles (Bac-NP), through ionic interactions, was used. It was hypothesized that the hybrid Bac- NP(Ang1) system can efficiently transduce hASCs and induces favorable therapeutic effects when transplanted in vivo. To evaluate this hypothesis, a rat model with acute myocardial infarction and intramyocardially transplanted Ang1-expressing hASCs (hASC-Ang1), genetically modified by Bac-NP(Ang1), was used. Ang1 is a crucial pro-angiogenic factor for vascular maturation and neovasculogenesis. The released hAng1 from hASC-Ang1 demonstrated profound mitotic and anti-apoptotic activities on endothelial cells and cardiomyocytes. The transplanted hASC-Ang1 group showed higher cell retention compared to hASC and control groups. A significant increase in capillary density and reduction in infarct sizes were noted in the infarcted hearts with hASC-Ang1 treatment compared to infarcted hearts treated with hASC or the untreated group. Furthermore, the hASC-Ang1 group showed significantly higher cardiac performance in echocardiography (ejection fraction 46.28% ± 6.3%, P < 0.001 versus control, n = 8) than the hASC group (36.35% ± 5.7%, P < 0.01, n = 8), 28 days post-infarction. The study identified Bac-NP complex as an advanced gene delivery vehicle for stem cells and demonstrated its potential to treat ischemic heart disease with high therapeutic index for combined stem cell-gene therapy strategy.
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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) | 0.000 | 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".