Biodegradable 3D-Printed Conjunctival Inserts for the Treatment of Dry Eyes
Bibliographic record
Abstract
PURPOSE: To fabricate 3D-printed, biodegradable conjunctival gelatin methacrylate (GelMA) inserts that can release polyvinyl alcohol (PVA) when exposed to an ocular surface enzyme. METHOD: In this work, biodegradable conjunctival inserts were 3D-printed using a stereolithography-based technique. The release of PVA from these insert formulations (containing 10% GelMA and 5% PVA (P-Gel-5%)) was assessed along with different mathematical models of drug release. The biodegradation rates of these inserts were studied in the presence of a tear-film enzyme (matrix metalloproteinase-9; MMP9). The morphology of the inserts before and after enzymatic degradation was monitored using scanning electron microscopy. RESULTS: The 3D-printed P-Gel-5% inserts formed a semi-interpenetrating network, which was mechanically stronger than GelMA inserts. The PVA release graphs demonstrate that at the end of 24 h, 222.7 ± 20.3 µg, 265.5 ± 27.1 µg, and 242.7 ± 30.4 µg of PVA were released when exposed to 25, 50, and 100 µg/mL of MMP9, respectively. The release profiles of the P-Gel-5% containing hydrogels in the presence of different concentrations of MMP9 showed the highest linearity with the Korsmeyer-Peppas model. The results suggest that the degradation rate over 24 h is a function of MMP9 enzyme concentration. Over 80% of P-Gel-5% inserts were degraded at the end of 8 h, 12 h, and 24 h in the presence of 100, 50, and 25 µg/mL MMP9 enzyme solutions, respectively. CONCLUSIONS: These results demonstrate the potential for 3D printing of GelMA for use as conjunctival inserts. These inserts could be used to deliver PVA, which is a well-known therapeutic agent for dry eye disease. PVA release is influenced by multiple mechanisms, including diffusion and enzymatic degradation, which is supported by morphological studies and biodegradation results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".