Photochemically Activated Notch Signaling Hydrogel Preferentially Differentiates Human Derived Hepatoblasts to Cholangiocytes
Bibliographic record
Abstract
Abstract Cholangiocytes form an intricate network of bile ducts to enable proper liver function; yet, recapitulating human stem cell differentiation to cholangiocytes in vitro requires Notch signaling and soluble ligands do not activate the Notch pathway. To overcome these limitations, jagged1 is immobilized on a chemically defined hyaluronan to specifically differentiate human embryonic stem cell‐derived hepatoblasts to cholangiocytes. Hepatoblasts cultured on the jagged1‐hydrogels upregulate Notch target genes and express key cholangiocyte markers including cystic fibrosis transmembrane conductance regulator. Moreover, cholangiocytes adopt morphological changes that resemble liver biliary structures. To emulate natural biliary system development, a new strategy is developed to achieve spatiotemporal control over the Jagged1–Notch2 interaction: jagged1 is first caged with a photocleavable streptavidin and then it is uncaged photochemically to restore the biological function of Jagged1, which is confirmed with Notch2 activation in a fluorescent reporter cell line. Moreover, the differentiation of human embryonic stem cell‐derived hepatoblasts to cholangiocytes is temporally controlled with photochemical uncaging of this streptavidin‐Jagged1‐immobilized hyaluronan hydrogel. This strategy defines a framework to control protein signaling in time and space and specifically for Notch signaling for ultimate use in regenerative medicine strategies of the liver.
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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) | 0.000 | 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) | 0.002 | 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".