Donor pigs for clinical islet xenotransplantation: Review and future directions
Bibliographic record
Abstract
Allogeneic islet transplantation becomes a viable option for patients with unstable type 1 diabetes. However, considering the huge number of patients with type 1 diabetes, human donor shortage is a serious issue. To overcome the donor shortage issue, xenotransplantation is an attractive option. In fact, clinical islet xenotransplantation has been conducted since 1990s. The first clinical trial was performed using fetal pigs and demonstrated the porcine pancreatic tissue could survive in human body with immunosuppressive strategies. To scale up the islet production, Canadian group established a method for islet isolation from neonatal pigs. Their method has been used for clinical islet xenotransplantation in New Zealand, Russian, Mexico, Argentina, and China. Recently Korean group published a clinical protocol for islet xenotransplantation using adult pigs. For the next generation of islet xenotransplantation, gene-modified pigs were created. Especially "superislets" created by Belgian group demonstrated promising preclinical outcomes. With advanced donor pigs, islet xenotransplantation might become a suitable treatment for the majority of type 1 diabetic patients.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".