High-risk corneal allografts: A therapeutic challenge
Bibliographic record
Abstract
Corneal transplantation is the most common surgical procedure amongst solid organ transplants with a high survival rate of 86% at 1-year post-grafting. This high success rate has been attributed to the immune privilege of the eye. However, mechanisms originally thought to promote immune privilege, such as the lack of antigen presenting cells and vessels in the cornea, are challenged by recent studies. Nevertheless, the immunological and physiological features of the cornea promoting a relatively weak alloimmune response is likely responsible for the high survival rate in "low-risk" settings. Furthermore, although corneal graft survival in "low-risk" recipients is favourable, the prognosis in "high-risk" recipients for corneal graft is poor. In "high-risk" grafts, the process of indirect allorecognition is accelerated by the enhanced innate and adaptive immune responses due to pre-existing inflammation and neovascularization of the host bed. This leads to the irreversible rejection of the allograft and ultimately graft failure. Many therapeutic measures are being tested in pre-clinical and clinical studies to counter the immunological challenge of "high-risk" recipients. Despite the prevailing dogma, recent data suggest that tissue matching together with use of systemic immunosuppression may increase the likelihood of graft acceptance in "high-risk" recipients. However, immunosuppressive drugs are accompanied with intolerance/side effects and toxicity, and therefore, novel cell-based therapies are in development which target host immune cells and restore immune homeostasis without significant side effect of treatment. In addition, developments in regenerative medicine may be able to solve both important short comings of allotransplantation: (1) graft rejection and ultimate graft failure; and (2) the lack of suitable donor corneas. The advances in technology and research indicate that wider therapeutic choices for patients may be available to address the worldwide problem of corneal blindness in both "low-risk" and "high-risk" hosts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".