Evaluation of transfection with gemini nanoparticles for retinal neuroprotection in a dynamic microfluidic cell culture system
Bibliographic record
Abstract
<img src=” https://s3.amazonaws.com/production.scholastica/article/94464/large/prnano_1252024ga.jpg?1709170827”> Glaucoma is a neurodegenerative disease of the retina and optic nerve with elevated intraocular pressure as one of the main contributing factors. The traditional in vitro methods to evaluate new gene delivery systems for neuroprotective treatments of glaucoma require testing in cell monolayers under static conditions. Therefore, a microfluidic technology that provides a dynamic simulation of cell exposure to nanoparticles (NPs) could be a useful model for rapid screening. In this study, CellASIC ONIX2 microfluidic platform was used to evaluate and optimize culture and transfection conditions to assess cell viability and transfection efficiency (TE) of gemini NPs carrying GFP-encoding plasmid in A7 astrocytes, one of the targeted retinal cells for glaucoma treatment. The average TE (inlet-middle-outlet of culture chambers) by gemini nanoplexes, 18-7NH-18 NPXs and 18-7Np3-18 NPXs was > 85% and > 25%, respectively, after 5 h of perfusion with a combined average FI (caFI) of about 600 and < 100, respectively, whereas TE after Lipofectamine 3000 was > 70% and caFI of < 100. The results have shown that comparatively to 2D monolayers, the microfluidics technique provides better exposure of cells to NPs, suitable for kinetic mapping of gene expression, and a useful tool for cell growth and live evaluation of gene delivery system interaction with cells.
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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 | 0.001 | 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".