Phenylboronic acid modified mucoadhesive nanoparticle drug carriers facilitate weekly treatment of experimentallyinduced dry eye syndrome
Bibliographic record
Abstract
Topical formulations, commonly applied for treatment of anterior eye diseases, require frequent administration due to rapid clearance from the ocular surface, typically through the lacrimal drainage system or through over-spillage onto the lids. We report on a mucoadhesive nanoparticle drug delivery system that may be used to prolong the precorneal residence time of encapsulated drugs. The nanoparticles were formed from self-assembly of block copolymers composed of poly( d, l -lactide) and Dextran. The enhanced mucoadhesion properties were achieved by surface functionalizing the nanoparticles with phenylboronic acid. The nanoparticles encapsulated up to 12 wt.% of Cyclosporine A (CycA) and sustained the release for up to five days at a clinically relevant dose, which led us to explore the therapeutic efficacy of the formulation with reduced administration frequency. By administering CycA-loaded nanoparticles to dry eye-induced mice once a week, inflammatory infiltrates were eliminated and the ocular surface completely recovered. The same once a week dosage of the nanoparticles also showed no signs of physical irritation or inflammatory responses in acute (1 week) and chronic (12 weeks) studies in healthy rabbit eyes. These findings indicate that the nanoparticles may significantly reduce the frequency of administration for effective treatment of anterior eye diseases without causing ocular irritation.
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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".