A20 as an immune tolerance factor can determine islet transplant outcomes
Bibliographic record
Abstract
Islet transplantation can restore lost glycemic control in type 1 diabetes subjects but is restricted in its clinical application by a limiting supply of islets and the need for heavy immune suppression to prevent rejection. TNFAIP3, encoding the ubiquitin editing enzyme A20, regulates the activation of immune cells by raising NF-κB signaling thresholds. Here, we show that increasing A20 expression in allogeneic islet grafts resulted in permanent survival for ~45% of recipients, and > 80% survival when combined with subtherapeutic rapamycin. Allograft survival was dependent upon Tregs and was antigen specific, and grafts showed reduced expression of inflammatory factors. Transplantation of islets with A20 containing a loss-of-function variant (I325N) resulted in increased RIPK1 ubiquitination and NF-κB signaling, graft hyperinflammation, and acute allograft rejection. Overexpression of A20 in human islets potently reduced expression of inflammatory mediators, with no impact on glucose-stimulated insulin secretion. Therapeutic administration of A20 raises inflammatory signaling thresholds to favor immune tolerance and promotes islet allogeneic survival. Clinically, this would allow for reduced immunosuppression and support the use of alternate islet sources.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".