Jagged2 acts as a Delta-like Notch ligand during early hematopoietic cell fate decisions
Bibliographic record
Abstract
Notch signaling critically mediates various hematopoietic lineage decisions and is induced in mammals by Notch ligands that are classified into 2 families, Delta-like (Delta-like-1, -3 and -4) and Jagged (Jagged1 and Jagged2), based on structural homology with both Drosophila ligands Delta and Serrate, respectively. Because the functional differences between mammalian Notch ligands were still unclear, we have investigated their influence on early human hematopoiesis and show that Jagged2 affects hematopoietic lineage decisions very similarly as Delta-like-1 and -4, but very different from Jagged1. OP9 coculture experiments revealed that Jagged2, like Delta-like ligands, induces T-lineage differentiation and inhibits B-cell and myeloid development. However, dose-dependent Notch activation studies, gene expression analysis, and promoter activation assays indicated that Jagged2 is a weaker Notch1-activator compared with the Delta-like ligands, revealing a Notch1 specific signal strength hierarchy for mammalian Notch ligands. Strikingly, Lunatic-Fringe- mediated glycosylation of Notch1 potentiated Notch signaling through Delta-like ligands and also Jagged2, in contrast to Jagged1. Thus, our results reveal a unique role for Jagged1 in preventing the induction of T-lineage differentiation in hematopoietic stem cells and show an unexpected functional similarity between Jagged2 and the Delta-like ligands.
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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) | 0.001 | 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 | 0.000 | 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".