Development of Mucoadhesive Thermogels for Treating Anterior Ocular Conditions
Bibliographic record
Abstract
Most marketed formulations for treating anterior ocular conditions are topical, with conventional eyedrops representing the most utilized modality. However, due to the natural clearance mechanisms of the eye, less than 5% of an applied dose remains bioavailable following administration. To overcome the shortcomings associated with conventional eyedrops, a series of enzymatically degradable, mucoadhesive thermogels were developed. Thermogels can be applied as a solution, like a conventional eyedrops, but gel against the heat of eye. To avoid obstructing vision, these thermogels were designed to be instilled within the inferior fornix of the eye. In these studies, the base thermogelling polymer (pNAM) was crosslinked with the natural polymer chitosan. Not only does crosslinking strengthen the typically weak thermogels, but chitosan can be enzymatically degraded by lysozyme, the highest concentration protein found in tear fluid. Therefore, the developed thermogels can be applied to the inferior fornix and degrade over multiple days. A limitation of applying materials to the inferior fornix is they tend to be poorly retained. To anchor the developed thermogels within the inferior fornix, the mucoadhesive properties were tailored based on the chitosan utilized as well as the inclusion of a disulfide monomer capable of covalently bonding with the natural mucosal layer covering the surface of the eye. The disulfide bridging monomer could be further conjugated with therapeutic components which were released as a function of mucosal interaction. Conjugates investigated included cysteamine for treating cystinosis, n-acetyl cysteine for treating dry eye, the adhesion peptide RGDC as a model peptide/protein, and polyethylene glycol for modulating material properties. The release of the drugs Ketotifen Fumarate, for treating allergic conjunctivitis, and atropine, for treating myopia, were also investigated. The safety of the developed thermogels were studied both in vivo and extensively in vitro utilizing both rat and rabbit models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".