Differentiation of Human Pluripotent Stem Cells into Insulin-Producing Islet Clusters
Bibliographic record
Abstract
Differentiation of human pluripotent stem cells (hPSCs) into insulin-secreting beta cells provides material for investigating beta cell function and diabetes treatment. However, challenges remain in obtaining stem cell-derived beta cells that adequately mimic native human beta cells. Building upon previous studies, hPSC-derived islet cells have been generated to create a protocol with improved differentiation outcomes and consistency. The protocol described here utilizes a pancreatic progenitor kit during Stages 1-4, followed by a protocol modified from a paper previously published in 2014 (termed "R-protocol" hereafter) during Stages 5-7. Detailed procedures for using the pancreatic progenitor kit and 400 µm diameter microwell plates to generate pancreatic progenitor clusters, R-protocol for endocrine differentiation in a 96-well static suspension format, and in vitro characterization and functional evaluation of hPSC-derived islets, are included. The complete protocol takes 1 week for initial hPSC expansion followed by ~5 weeks to obtain insulin-producing hPSC islets. Personnel with basic stem cell culture techniques and training in biological assays can reproduce this protocol.
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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 | 0.001 |
| 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) | 0.005 | 0.003 |
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".