An Endothelial Cell Niche Induces Hepatic Specification Through Dual Repression of Wnt and Notch Signaling
Bibliographic record
Abstract
Complex cross-talk between endoderm and the microenvironment is an absolute requirement to orchestrate hepatic specification and expansion. In the mouse, the septum transversum and cardiac mesoderm, through secreted bone morphogenetic proteins (BMP) and fibroblast growth factors (FGF), respectively, instruct the adjacent ventral endoderm to become hepatic endoderm. Consecutively, endothelial cells promote expansion of the specified hepatic endoderm. By using a mouse reporter embryonic stem cell line, in which hCD4 and hCD25 were targeted to the Foxa2 and Foxa3 loci, we reconstituted an in vitro culture system in which committed endoderm cells coexpressing hCD4-Foxa2 and hCD25-Foxa3 were isolated and cocultured with endothelial cells in the presence of BMP4 and bFGF. In this culture setting, we provide mechanistic evidence that endothelial cells function not only to promote hepatic endoderm expansion but are also required at an earlier step for hepatic specification, at least in part through regulation of the Wnt and Notch pathways. Activation of Wnt and Notch by chemical or genetic approaches increases endoderm cell numbers but inhibits hepatic specification, and conversely, chemical inhibition of both pathways enhances hepatic specification and reduces proliferation. By using identical coculture conditions, we defined a similar dependence of endoderm harvested from embryos on endothelial cells to support their growth and hepatic specification. Our findings (1) confirm a conserved role of Wnt repression for mouse hepatic specification, (2) uncover a novel role for Notch repression in the hepatic fate decision, and (3) demonstrate that repression of Wnt and Notch signaling in hepatic endoderm is controlled by the endothelial cell niche.
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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 | 0.000 |
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 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".