Characterization of stem-cell-derived islets during differentiation and after implantation
Bibliographic record
Abstract
Recapitulation of embryonic pancreatic development has enabled development of methods for in vitro islet cell differentiation using human pluripotent stem cells (hPSCs), which have the potential to cure diabetes. Advanced methods for optimal generation of stem-cell-derived islets (SC-islets) has enabled successful diabetes reversal in rodents and shown promising early clinical trial outcomes. The main impediment for use of SC-islets is concern about safety because of off-target growth resulting from contaminated residual cells. In this review, we summarize the different endocrine and non-endocrine cell populations that have been described to emerge throughout β cell differentiation and after transplantation. We discuss the most recent approaches to enrich endocrine populations and remove off-target cells. Finally, we discuss the critical quality control and release criteria testing that we anticipate will be required prior to transplantation to ensure product safety.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 teacher head, 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".