Bibliographic record
Abstract
Cornea blindness is still treated mainly by corneal transplantation, using donated allograft human corneas. However, a severe global shortfall leaves an estimated 12.7 million patients on waiting lists despite methods of using one cornea for two different partial‐thickness grafts. Even more individuals are not on waiting lists because they have no access to transplantation in their countries or regions. However, even if donor tissues were readily available, patients with inflamed, severely damaged corneas are at high risk of rejecting conventional transplantation. Various solutions have been proposed as alternatives to corneal allografting, including the development of keratoprostheses and stem cell grafting. We posited using cell‐free implants that mimic the extracellular matrix of the human cornea to recapitulate the environment during corneal development and stimulate the endogenous cells within the patient's eyes to affect regeneration. We used cell‐free corneal implants made from chemically crosslinked recombinant human collagen to promote in situ tissue regeneration in pathologic corneas, including high‐risk ones. We successfully developed and tested recombinant human solid collagen‐based implants that promoted stable regeneration in inflamed human patient corneas based on phosphorylcholine (MPC). However, solid corneas require a full operating theatre and staffing, which is costly and not accessible to more remote regions in Canada and globally. Burns and severe infections that can lead to perforations are medical emergencies that require immediate methods to seal the eye. In many centres, cyanoacrylate glue is used as a sealant, but this is toxic and kills surrounding cells, often necessitating follow‐on transplantation. We developed a synthetic, biocompatible, and adhesive liquid hydrogel (LiQD Cornea), which would replace these toxic cyanoacrylate glues. LiQD cornea is applied as a liquid but quickly adheres and gels within corneal tissue defects like a dental filling. It can be used to fill ulcers and other damaged areas. Then its similarity at a molecular level to a natural tissue framework promotes tissue regeneration, treating corneal perforations effectively without transplantation. Further, due to the synthetic nature of the material, risks associated with disease transmission are reduced compared to natural products. We see LiQD Cornea potentially used in outpatient clinics instead of operating theatres, maximizing practicality and minimizing health care costs.
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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) | 0.001 | 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 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".