Role of Recycling, Mindbomb1 Association, and Exclusion from Lipid Rafts of Delta-like 4 for Effective Notch Signaling To Drive T Cell Development
Bibliographic record
Abstract
Intrathymic T cell development is predicated on the Notch1 ligand Delta-like (Dll) 4. However, both Dll4 and Dll1 can support T cell development in vitro. Endocytosis of Dll1 is important for Notch activation, whereas currently there is no evidence for the role of Dll4 endocytosis in T cell development. To elucidate this, we generated Dll4 constructs that modify or inhibit endocytosis. Our results show that targeting the intracellular domain affects Dll4's ability to induce Notch target gene expression, support efficient T cell development, and inhibit B cell development. Dll4 function relies on a combination of factors, which include strong Mindbomb1 (Mib1) association, ubiquitination, and internalization and recycling back to the cell surface, to engage Notch1 effectively. Distinct membrane localization and the Delta/Serrate/Lag2 (DSL) domain were important for Dll4 function. These features are consistent with a "recycling" model, but not in opposition to a "mechano-transduction" model, whereby Dll4 is able to engage Notch and create a pulling force required to activate signaling, leading to the induction of T-lineage development. Taken together, in contrast to Dll1, Dll4 does not localize to lipid rafts and shows stronger association with Mib1 and increased Notch1 uptake, which likely account for its superior ability to induce T cell development.
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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 | 0.000 | 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".