Clinical islet transplant: current and future directions towards tolerance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The ultimate goal of islet transplantation is to completely correct the diabetic state from an unlimited donor source, without the need for chronic immunosuppressive drug therapy. Although islet transplantation provides an opportunity to develop innovative strategies for tolerance in the clinic, both alloimmune and autoimmune barriers must be controlled, if stable graft function is to be maintained long-term. After islet extraction from the pancreas, the cellular graft may be stored in tissue culture or cryopreserved for banking, providing an opportunity not only to optimally condition the recipient but also to allow in vitro immunologic manipulation of the graft before transplantation, unlike solid organ grafts. As such, islets may be considered a "special case." Remarkable progress has occurred in the last three years, with dramatic improvements in outcomes after clinical islet transplantation. The introduction of a steroid-free, sirolimus-based, anti-rejection protocol and islets prepared from two (or rarely three) donors led to high rates of insulin independence. The "Edmonton Protocol" has been successfully replicated by other centers in an international multicenter trial. A number of key refinements in pancreas transportation, processing, purification on non-ficoll-based media, storage of islets in culture for two days and newer immunological conditioning and induction therapies have led to continued advancement through extensive collaboration between key centers. This review outlines the historical development of islet transplantation over the past 30 years, provides an update on current clinical outcomes, and summarizes a series of unique opportunities for development and early testing of tolerance protocols in 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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it