Formulation of siRNA nanoparticles, transfection and enhanced adhesion -penetration in nasal mucosal tissue
Bibliographic record
Abstract
This study investigates the efficacy of trimethyl chitosan (TMC) nanoparticles (NPs) for the delivery of small interfering RNA (siRNA) targeting the EGFR gene, with a focus on optimizing complexation efficiency, release profiles, and transfection efficiency, as well as investigating mucoadhesion and mucopenetration properties. TMC nanoparticles were formulated at various siRNA:TMC weight-to-weight (w:w) ratios and assessed for binding efficiency, release in the presence of heparin, physical properties, cytotoxicity, and EGFR knockdown efficiency in HeLa cells. The integration of additives such as dextran sulfate (DS), tripolyphosphate (TPP), and hyaluronic acid (HA) was explored to enhance nanoparticle performance. Results demonstrated that higher TMC ratios improved siRNA binding and reduced release rates, with additives further stabilizing the nanoparticles. The optimized formulations showed high cell viability and significant EGFR silencing, indicating effective transfection. Mucoadhesion and mucopenetration two-photon microscopy studies on rabbit nasal mucosa confirmed the superior performance of TMC nanoparticles over free siRNA, highlighting their potential for non-invasive gene therapy applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".