Current Topics of Relevance to the Xenotransplantation of Free Pig Islets
Bibliographic record
Abstract
Pig islet xenotransplantation is a potential treatment for patients with type 1 diabetes. Current efforts are focused on identifying the optimal pig islet source and overcoming the immunological barrier. The optimal age of the pig donors remains controversial since both adult and neonatal pig islets have advantages. Isolation of adult islets using GMP grade collagenase has significantly improved the quantity and quality of adult islets, but neonatal islets can be isolated at a much lower cost. Certain culture media and coculture with mesenchymal stromal cells facilitate neonatal islet maturation and function. Genetic modification in pigs affords a promising strategy to prevent rejection. Deletion of expression of the three known carbohydrate xenoantigens (Gal, Neu5Gc, Sda) will certainly be beneficial in pig organ transplantation in humans, but this is not yet proven in islet transplantation, though the challenge of the ‘4th xenoantigen’ may prove problematic in nonhuman primate models. Blockade of the CD40/CD154 costimulation pathway leads to long-term islet graft survival (of up to 965 days). Anti-CD40mAbs have already been applied in phase II clinical trials of islet allotransplantation. Fc region-modified anti-CD154mAbs successfully prevent the thrombotic complications reported previously. In this review, we discuss (I) the optimal age of the islet-source pig, (ii) progress in genetic modification of pigs, (iii) the immunosuppressive regimen for pig islet xenotransplantation, and (iv) the reduction in the instant blood-mediated inflammatory reaction.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".