Mucoadhesive thermogel platform for treating anterior ocular conditions
Bibliographic record
Abstract
A platform mucoadhesive and thermogelling eyedrop was developed for application to the inferior fornix for the treatment of various anterior segment ocular conditions. The poly(n-isopropylacrylamide) polymers (pNIPAAm), containing a disulfide bridging monomer, were crosslinked with chitosan to yield a modifiable, mucoadhesive, and natively degradable thermogelling system. Three different conjugates were studied including a small molecule for treating dry eye, an adhesion peptide for modeling delivery of peptides/proteins to the anterior eye, and a material property modifier to create gels with different rheologic characteristics. Based on the conjugate used, different material properties such as solution viscosity and lower critical solution temperature (LCST) were produced. In addition to releasing the conjugates through disulfide bridging with ocular mucin, the thermogels were shown to deliver atropine, with 70%-90% being released over 24-h, depending on the formulation studied. The results illustrate that these materials can deliver multiple therapeutic payloads at one time and release them through various mechanisms. Finally, the safety and tolerability of the thermogels was demonstrated both in vitro and in vivo. The gels were instilled into the inferior fornix of rabbits and were shown to not produce any adverse effects over 4 days. These materials were demonstrated to be highly tunable, creating a platform that could be easily modified to deliver various therapeutic agents to treat a multitude of ocular diseases and have the potential to be an alternative to conventional eyedrops.
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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 | 0.001 |
| 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".