The Current Status of Allogenic Islet Cell Transplantation
Bibliographic record
Abstract
Type 1 Diabetes (T1D) is an autoimmune destruction of pancreatic beta cells. The development of the Edmonton Protocol for islet transplantation in 2000 revolutionized T1D treatment and offered a glimpse at a cure for the disease. In 2022, the 20-year follow-up findings of islet cell transplantation demonstrated the long-term safety of islet cell transplantation despite chronic immunosuppression. The Edmonton Protocol, however, remains limited by two obstacles: scarce organ donor availability and risks associated with chronic immunosuppression. To overcome these challenges, the search has begun for an alternative cell source. In 2006, pluripotency genomic factors, coined "Yamanaka Factors," were discovered, which reprogram mature somatic cells back to their embryonic, pluripotent form (iPSC). iPSCs can then be differentiated into specialized cell types, including islet cells. This discovery has opened a gateway to a personalized medicine approach to treating diabetes, circumventing the issues of donor supply and immunosuppression. In this review, we present a brief history of allogenic islet cell transplantation from the early days of pancreatic remnant transplantation to present work on encapsulating stem cell-derived cells. We review data on long-term outcomes and the ongoing challenges of allogenic islet cell and stem cell-derived islet cell transplant.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".