Islet transplantation for diabetes: current status and future prospects
Bibliographic record
Abstract
There has been an explosion of interest in developing transplantation strategies to replace the islets lost during the normal progression of diabetes. In large part, the renewed interest is due to the unprecedented success of the 'Edmonton protocol' for Type I diabetics following islet allografting and a modified 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 a concerted effort to develop novel means to enable islet transplantation on a widespread basis. This review outlines several of these possibilities including the development of novel, less toxic immunosuppressants, tolerising the host immune system to accept islet transplants, developing alternative sources of islet cells via gene therapy, stem cell technologies and xenotransplantation, immunoisolation of islets and providing local immunosuppression to islet grafts using Sertoli cells. These possibilities are highlighted in the context of islet cell transplantation as a success, but with need for further refinements before it is a panacea for most patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.000 | 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".