Complete Suspension Differentiation of Human Pluripotent Stem Cells into Pancreatic Islets Using Vertical Wheel <sup>®</sup> Bioreactors
Bibliographic record
Abstract
Abstract Advanced protocols to produce human pluripotent stem cell (SC)-derived islets show promise in functional, metabolic, and transcriptional maturation of cell therapy product to treat diabetes. Available protocols are either developed as complete planar (2D) or, in later stages, combined with suspension cultures (3D). Despite marked progress, both approaches have clear limitations for scalability, cell loss and batch to batch heterogeneity during differentiation. Using a Vertical Wheel ® bioreactor system, we present a highly efficient and scalable complete suspension protocol across all stages for directed differentiation of human pluripotent stem cells into functional pancreatic islets. Here, we generate homogeneous, metabolically functional, and transcriptionally enriched SC-islets and compared against adult donor islets. Generated SC-islets showed enriched endocrine cell composition (∼63% CPEP + NKX6.1 + ISL1 + ) and displayed functional maturity for glucose stimulated insulin secretion (∼5-fold) during in vitro and post transplantation. Comprehensive stage-specific single-cell mass flow cytometry characterization with dimensional reduction analysis at stage-4 and -6 confirmed optimal maturation was achieved without heterogeneity. Notably, by 16-weeks transplantation follow-up, normal glycemic homeostasis was restored, and glucose responsive human c-peptide secretion response (2-fold) was achieved. Four months post engraftment, graft-harvested single cells displayed islet hormonal cell composition with flow cytometry, improved functional maturity by in vivo glucose-stimulated insulin secretion (GSIS) and enhanced transcriptional landscape with real-time expression that closely resembled patterns comparable to adult human islets. Our comprehensive evaluation of a complete suspension method applied across all stages using Vertical Wheel ® bioreactors for SC-islets generation highlight progressive molecular and functional maturation of islets while reducing potential cell loss and cellular heterogeneity. Such a system could potentially be scaled to deliver clinical grade SC-islet products in a closed good manufacturing practice type environment. One Sentence Summary This study describes all-stages complete suspension protocol for SC-islets generation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
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".