Stable corneal regeneration four years after implantation of a cell-free recombinant human collagen scaffold
Bibliographic record
Abstract
We developed cell-free implants, comprising carbodiimide crosslinked recombinant human collagen (RHC), to enable corneal regeneration by endogenous cell recruitment, to address the worldwide shortage of donor corneas. Patients were grafted with RHC implants. Over four years, the regenerated neo-corneas were stably integrated without rejection, without the long immunosuppression regime needed by donor cornea patients. There was no recruitment of inflammatory dendritic cells into the implant area, whereas, even with immunosuppression, donor cornea recipients showed dendritic cell migration into the central cornea and a rejection episode was observed. Regeneration as evidenced by continued nerve and stromal cell repopulation occurred over the four years to approximate the micro-architecture of healthy corneas. Histopathology of a regenerated, clear cornea from a regrafted patient showed normal corneal architecture. Donor human cornea grafted eyes had abnormally tortuous nerves and stromal cell death was found. Implanted patients had a 4-year average corrected visual acuity of 20/54 and gained more than 5 Snellen lines of vision on an eye chart. The visual acuity can be improved with more robust materials for better shape retention. Nevertheless, these RHC implants can achieve stable regeneration and therefore, represent a potentially safe alternative to donor organ transplantation.
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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 | 0.000 |
| 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 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".