Mucoadhesive Polymers Enhance Ocular Drug Delivery: Proof of Concept Study with 0.5% Tropicamide in Dogs
Bibliographic record
Abstract
Purpose: To assess the efficacy of 0.5% tropicamide applied after topical administration of 1.4% hydroxyethyl cellulose (HEC) or 1.2% hyaluronic acid (HA) at different time intervals. Methods: Eleven healthy Labrador retriever dogs were used. The study consisted of 7 trials in which pupil diameter (PD) was measured every 30 min for 7 h after drug administration. In trial 1, PD was measured after tropicamide application (control). In trials 2–7, PD was measured after treatment with tropicamide 10 s, 1 and 5 min after application of HEC or HA. Data were analyzed using analysis of variance and post hoc Holm-Sidak tests. Results: Maximal PD (mean ± standard deviation) was significantly greater ( P < 0.001) in 5 of 6 experimental trials, with the greatest PD recorded when HEC was applied 1 min (12.2 ± 0.4 mm) and HA 10 s (12.3 ± 0.5 mm) before tropicamide, compared with 11.2 ± 0. 7 mm in control trial 1. PD >10 mm was maintained for 2.75–5 h in trials 2–7 and 2.25 h in trial 1 ( P < 0.001). Area under the PD–time curve ranged from 61.9 to 71.3 ± 2.9 mm·hours in trials 2–7, significantly greater than 59.3 ± 1.8 mm·hours in control trial 1 ( P ≤ 0.031). Conclusions: Tropicamide efficacy was enhanced by prior administration of a mucoadhesive polymer. Additional studies are needed to determine if HEC and HA of varying concentrations similarly extend and potentiate the effect of other topical ophthalmic drugs in canine eyes.
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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 | 0.001 | 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 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".