Developmentally-Inspired Biomimetic Culture Models to Produce Functional Islet-Like Cells From Pluripotent Precursors
Bibliographic record
Abstract
Insulin-producing beta cells sourced from pluripotent stem cells hold great potential as a virtually unlimited cell source to treat diabetes. Directed pancreatic differentiation protocols aim to mimic various stimuli present during embryonic development through sequential changes of in vitro culture conditions. This is commonly accomplished by the timed addition of soluble signaling factors, in conjunction with cell-handling steps such as the formation of 3D cell aggregates. Interestingly, when stem cells at the pancreatic progenitor stage are transplanted, they form functional insulin-producing cells, suggesting that in vivo microenvironmental cues promote beta cell specification. Among these cues, biophysical stimuli have only recently emerged in the context of optimizing pancreatic differentiation protocols. This review focuses on studies of cell-microenvironment interactions and their impact on differentiating pancreatic cells when considering cell signaling, cell-cell and cell-ECM interactions. We highlight the development of in vitro cell culture models that allow systematic studies of pancreatic cell mechanobiology in response to extracellular matrix proteins, biomechanical effects, soluble factor modulation of biomechanics, substrate stiffness, fluid flow and topography. Finally, we explore how these new mechanical insights could lead to novel pancreatic differentiation protocols that improve efficiency, maturity, and throughput.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".