Metalloproteinase inhibitors regulate biliary progenitor cells through sDLK1 in organoid models of liver injury
Bibliographic record
Abstract
Understanding cell fate regulation in the liver is necessary to advance cell therapies for hepatic disease. Liver progenitor cells (LPCs) contribute to tissue regeneration after severe hepatic injury, yet signals instructing progenitor cell dynamics and fate are largely unknown. Tissue inhibitor of metalloproteinases 1 (TIMP1) and TIMP3 control the sheddases ADAM10 and ADAM17, key for NOTCH activation. Here we uncover the role of the TIMP/ADAM/NOTCH/DLK1 axis in LPC maintenance and cholangiocyte specification. Combined TIMP1/TIMP3 loss in vivo caused abnormal portal triad stoichiometry accompanied by collagen deposits, dysregulated Notch signaling, and increased soluble DLK1. The MIC1-1C3+CD133+CD26- biliary progenitor population was reduced following acute CCl4 or chronic DDC liver injury and in aged TIMP-deficient livers. Single-cell RNA sequencing data interrogation and RNAscope identified portal mesenchymal cells coexpressing ADAM17/DLK1 as enzymatically equipped to process DLK1 and direct LPC differentiation. Specifically, TIMP-deficient biliary fragment-derived organoids displayed increased propensity for cholangiocyte differentiation. ADAM17 inhibition reduced Sox9-mediated cholangiocyte differentiation, prolonging organoid growth and survival, whereas WT organoids treated with soluble DLK1 triggered Sox9 expression and cholangiocyte specification in mouse and patient-derived liver organoids. Thus, metalloproteinase inhibitors regulate instructive signals for biliary cell differentiation and LPC preservation within the portal niche, providing a new basis for cell therapy strategies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".