The future treatment for type 1 diabetes: Pig islet- or stem cell-derived β cells?
Bibliographic record
Abstract
Replacement of β cells is only a curative approach for type 1 diabetes (T1D) patients to avoid the threat of iatrogenic hypoglycemia. In this pursuit, islet allotransplantation under Edmonton's protocol emerged as a medical miracle to attain hypoglycemia-free insulin independence in T1D. Shortage of allo-islet donors and post-transplantation (post-tx) islet loss are still unmet hurdles for the widespread application of this therapeutic regimen. The long-term survival and effective insulin independence in preclinical studies have strongly suggested pig islets to cure overt hyperglycemia. Importantly, CRISPR-Cas9 technology is pursuing to develop "humanized" pig islets that could overcome the lifelong immunosuppression drug regimen. Lately, induced pluripotent stem cell (iPSC)-derived β cell approaches are also gaining momentum and may hold promise to yield a significant supply of insulin-producing cells. Theoretically, personalized β cells derived from a patient's iPSCs is one exciting approach, but β cell-specific immunity in T1D recipients would still be a challenge. In this context, encapsulation studies on both pig islet as well as iPSC-β cells were found promising and rendered long-term survival in mice. Oxygen tension and blood vessel growth within the capsules are a few of the hurdles that need to be addressed. In conclusion, challenges associated with both procedures, xenotransplantation (of pig-derived islets) and stem cell transplantation, are required to be cautiously resolved before their clinical application.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".