PAMAM Dendrimer-Baculovirus Nanocomplex for Microencapsulated Adipose Stem Cell-Gene Therapy: <i>In Vitro</i> and <i>in Vivo</i> Functional Assessment
Bibliographic record
Abstract
The present study aims to develop a new stem cell based gene delivery system consisting of human adipose tissue derived stem cells (hASCs) genetically modified with self-assembled nanocomplex of recombinant baculovirus and PAMAM dendrimer (Bac-PAMAM) to overexpress the vascular endothelial growth factor (VEGF). Cells were enveloped into branched PEG surface functionalized polymeric microcapsules for efficient transplantation. In vitro analysis confirmed efficient transduction of hASCs expressing 7.65 ± 0.86 ng functionally active VEGF per 10(6) microencapsulated hASCs (ASC-VEGF). To determine the potential of the developed system, chronically infarcted rat hearts were treated with either empty microcapsules (MC), microencapsulated hASCs expressing MGFP reporter protein (MC+ASC-MGFP), or MC+ASC-VEGF, and analyzed for 10 weeks. Post-transplantation data confirmed higher myocardial VEGF expressions with significantly enhanced neovasculature in the MC+ASC-VEGF group. In addition, the cardiac performance, as measured by percentage ejection fraction, also improved significantly in the MC+ASC-VEGF group (48.6 ± 6.1%) compared to that in MC+ASC-MGFP (38.8 ± 5.3%) and MC groups (31.5 ± 3.3%). Collectively, these data demonstrate the feasibility of this system for improved stem cell therapy applications.
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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) | 0.000 | 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".