Retinal transplantation: progress and problems in clinical application
Bibliographic record
Abstract
There is currently no real treatment for blinding disorders that stem from the degeneration of cells in the retina and affect at least 50 million individuals worldwide. The excitement that accompanied the first studies showing the potential of retinal cell transplantation to alleviate the progress of blindness in such diseases as retinitis pigmentosa and age-related macular degeneration has lost some of its momentum, as attempts to apply research to the clinic have failed so far to provide effective treatments. What these studies have shown, however, is not that the approach is flawed but rather that the steps that need to be taken to achieve a viable, clinical treatment are many. This review summarizes the course of retinal transplant studies and points to obstacles that still need to be overcome to improve graft survival and efficacy and to develop a protocol that is effective in a clinical setting. Emphasis is given particularly to the consequences of introducing transplants to sites that have been considered immunologically privileged and to the role of the major histocompatibility complex classes I and II molecules in graft survival and rejection.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".