Islet Xenotransplantation Using Gal-Deficient Neonatal Donors Improves Engraftment and Function
Bibliographic record
Abstract
Significant deficiencies in understanding of xenospecific immunity have impeded the success of preclinical trials in xenoislet transplantation. Although galactose-α1,3-galactose, the gal epitope, has emerged as the principal target of rejection in pig-to-primate models of solid organ transplant, the importance of gal-specific immunity in islet xenotransplant models has yet to be clearly demonstrated. Here, we directly compare the immunogenicity, survival and function of neonatal porcine islets (NPIs) from gal-expressing wild-type (WT) or gal-deficient galactosyl transferase knockout (GTKO) donors. Paired diabetic rhesus macaques were transplanted with either WT (n = 5) or GTKO (n = 5) NPIs. Recipient blood glucose, transaminase and serum xenoantibody levels were used to monitor response to transplant. Four of five GTKO versus one of five WT recipients achieved insulin-independent normoglycemia; transplantation of WT islets resulted in significantly greater transaminitis. The WT NPIs were more susceptible to antibody and complement binding and destruction in vitro. Our results confirm that gal is an important variable in xenoislet transplantation. The GTKO NPI recipients have improved rates of normoglycemia, likely due to decreased susceptibility of xenografts to innate immunity mediated by complement and preformed xenoantibody. Therefore, the use of GTKO donors is an important step toward improved consistency and interpretability of results in future xenoislet studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".