Investigating the Effect of a Micelle-Based Drug Delivery System in Reducing IOP and Glaucomatous Effects in a Partially Open Angle Mouse Model of Glaucoma
Bibliographic record
Abstract
This project explores the use of a novel sustained release mucoadhesive micelle-based drug delivery system in combination with 0.005% latanoprost (LTP) on our partially open angle mouse model of glaucoma (AP-2β TMR-KO). We previously tested for LTP treatment in our model and found a reduction in intraocular pressure (IOP) 20 minutes following treatment. This information led us to investigate the long-term effect of LTP treatment and micelle loaded with LTP (MLTP) treatment in our model. We hypothesized that the MLTP treatment would be more effective in reducing IOP and preventing glaucomatous effects than LTP treatment alone in the AP-2β TMR-KO mice. The MLTP groups of animals (wildtype and mutant) were treated every 3 days, and this was compared with animals treated with LTP daily as well as animals treated every 3 days with LTP alone for comparison’s sake for 60 days. IOP measurements were taken every 3 days. Following long term LTP treatment alone, mutant mice showed a consistent decrease in their baseline IOPs with a significant reduction in baseline IOP at 35 days of treatment across all cohorts (P<0.0001). In comparison, mutants treated with MLTP exhibited an even greater reduction in baseline IOP following long term treatment. After the treatment period, mice were euthanized, and their eyes were enucleated, fixed, sectioned, and stained for retinal ganglion cells (RGCs) using Brn3a. Mutant mice exhibited a significant decrease in RGC cell number when compared to wildtype, and this loss was not rescued by treatment with LTP. However, mutants treated with MLTP demonstrated significant RGC cell protection compared to eyes of untreated mutants, as well as everyday LTP treated mutants.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".