Lunatic Fringe Enhances Competition for Delta-Like Notch Ligands but Does Not Overcome Defective Pre-TCR Signaling during Thymocyte β-Selection In Vivo
Bibliographic record
Abstract
Notch1 activation by Delta-like (DL) Notch ligands is essential to induce T cell commitment and to suppress B cell development from thymus-seeding progenitors. Thymus-seeding progenitor competition for DL4 is critically regulated by Lunatic Fringe (Lfng), which glycosylates epidermal growth factor repeats in the Notch1 extracellular domain to enhance binding avidity for DL ligands. Notch1 activation is also essential for the process of β-selection, which drives TCRβ(+) CD4/CD8 double-negative 3 (DN3) precursors to proliferate and generate a large pool of CD4/CD8 double-positive thymocytes. We have used several genetic approaches to determine the importance of Lfng-Notch1 interactions in regulating competition of preselection and postselection DN3 thymocytes for DL ligands in vivo. Surprisingly, although Lfng overexpression enhanced DL4 binding by preselection DN3a thymocytes, it did not confer them with a competitive advantage in mixed chimeras. In contrast, Lfng overexpression enhanced competition of post-β-selection DN3b precursors for DL ligands. Lfng modification of O-fucose in the Notch1 ligand-binding domain contributed to but was not solely responsible for the developmental effects of Lfng overexpression. Although previous studies have suggested that pre-TCR-deficient DN3 thymocytes compete poorly for DL ligands, Lfng overexpression did not fully restore double-positive thymocyte pools from DN3b cells with pre-TCR signaling defects. Thus, pre-TCR and Notch signaling have largely nonoverlapping functions in β-selection. Collectively, our data reveal that Lfng enhances DN3b precursor competition for intrathymic DL ligands to maximize Notch-induced clonal expansion during the earliest stage of β-selection.
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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 | 0.001 | 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) | 0.000 | 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".