Biodegradable Film for the Targeted Delivery of siRNA-Loaded Nanoparticles to Vaginal Immune Cells
Bibliographic record
Abstract
The goal of this study was to develop and characterize a novel intravaginal film platform for targeted delivery of small interfering RNA (siRNA)-loaded nanoparticles (NP) to dendritic cells as a potential gene therapy for the prevention of sexually transmitted human immunodeficiency virus (HIV) infection. Poly(ethylene glycol) (PEG)-functionalized poly(D, L-lactic-co-glycolic acid) (PLGA)/polyethylenimine (PEI)/siRNA NP (siRNA-NP) were fabricated using a modified emulsion-solvent evaporation method and characterized for particle size, zeta potential, encapsulation efficiency (EE), and siRNA release. siRNA-NP were decorated with anti-HLA-DR antibody (siRNA-NP-Ab) for targeting delivery to HLA-DR+ dendritic cells (DCs) and homogeneously dispersed in a biodegradable film consisting of poly vinyl alcohol (PVA) and λ-carrageenan. The siRNA-NP-Ab-loaded film (siRNA-NP-Ab-film) was transparent, displayed suitable physicomechanical properties, and was noncytotoxic. Targeting activity was evaluated in a mucosal coculture model consisting of a vaginal epithelial monolayer (VK2/E6E7 cells) and differentiated KG-1 cells (HLA-DR+ DCs). siRNA-NP-Ab were rapidly released from the film and were able to penetrate the epithelial layer to be taken up by differentiated KG-1 cells. siRNA-NP-Ab demonstrated higher targeting activity and significantly higher knockdown of synaptosome-associated 23-kDa protein (SNAP-23) mRNA and protein when compared to siRNA-NP without antibody conjugation. Overall, these data suggest that our novel siRNA-NP-Ab-film may be a promising platform for preventing HIV infection within the female genital tract.
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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) | 0.001 | 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".