Harnessing the Immunomodulatory Properties of Sertoli Cells to Enable Xenotransplantation in Type I Diabetes
Bibliographic record
Abstract
Islet transplantation has emerged as a viable long-term means of treating type I diabetes. This is largely due to the success of the "Edmonton protocol" which has produced insulin independence in 85% of patients 1 year after transplantation of allogeneic islets together with a non-steroid immunosuppressive regimen. While these data provide a clear and unequivocal demonstration that islet transplantation is a viable treatment strategy, the shortage of suitable donor tissue together with the debilitating consequences of life-long immunosuppression necessitate the development of novel means to enable transplantation of all type 1 diabetics including the young juvenile diabetics. One potential means of enabling islet transplantation takes advantage of the ability of Sertoli cells to provide local immunoprotection to co-grafted islets, including those from xenogeneic sources. Sertoli cells are normally found in the testes where one of their functions is to provide local immunologic protection to developing germ cells. In animal models, allogeneic and xenogeneic islets survive and function for extended periods of time when grafted into the testes. Moreover, isolated Sertoli cells protect co-grafted allogeneic and xenogeneic islets from immune destruction and reverse diabetes in immunocompetent and autoimmune animals. These benefits are discussed in the context of several potential underlying biological mechanisms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".