Bioengineered 3D hPSC-cholangiocyte ducts with physiological signals for biliary disease modelling
Bibliographic record
Abstract
Abstract The progression of intrahepatic biliary diseases remains poorly understood, underscoring the urgent need to develop physiologically relevant human intrahepatic cholangiocyte disease models. Current approaches lack the complexity and throughput to capture how diverse biliary microenvironmental signals shape cholangiocyte behavior. To address this gap, we created a fully epithelialized and perfusible 3D bile duct from human pluripotent stem cell-derived cholangiocytes characterized by robust primary ciliation, apical-basal polarity and CFTR-mediated chloride conductance. Our results revealed physiologically relevant fluid flow and biliary stroma cells as essential components for sustaining cholangiocyte epithelial barrier integrity and ciliation. From here, we interrogated a broad spectrum of biliary signals to study bile acid toxicity and cytokine-driven injury, offering an unprecedented view into intrahepatic cholangiocyte stress responses and potential pathological mechanisms. By integrating physiologically relevant signals, fidelity and functional resolution, this platform provides the foundation needed to precisely decode pathogenic drivers and accelerate therapeutic development for devastating cholangiopathies. Graphical Abstract
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".