Lunatic, Manic, and Radical Fringe Each Promote T and B Cell Development
Bibliographic record
Abstract
Lunatic, Manic, and Radical Fringe (LFNG, MFNG, and RFNG) are N-acetylglucosaminyltransferases that modify Notch receptors and regulate Notch signaling. Loss of LFNG affects thymic T cell development, and LFNG and MFNG are required for marginal zone (MZ) B cell development. However, roles for MFNG and RFNG in T cell development, RFNG in B cell development, or Fringes in T and B cell activation are not identified. In this study, we show that Lfng/Mfng/Rfng triple knockout (Fng tKO) mice exhibited reduced binding of DLL4 Notch ligand to CD4/CD8 double-negative (DN) T cell progenitors, and reduced expression of NOTCH1 targets Deltex1 and CD25. Fng tKO mice had reduced frequencies of DN1/cKit(+) and DN2 T cell progenitors and CD4(+)CD8(+) double-positive (DP) T cell precursors, but increased frequencies of CD4(+) and CD8(+) single-positive T cells in the thymus. In spleen, Fng tKO mice had reduced frequencies of CD4(+), CD8(+), central memory T cells and MZ B cells, and an increased frequency of effector memory T cells, neutrophils, follicular, and MZ P B cells. The Fng tKO phenotype was cell-autonomous and largely rescued in mice expressing one allele of a single Fng gene. Stimulation of Fng tKO splenocytes with anti-CD3/CD28 beads or LPS gave reduced proliferation compared with controls, and the generation of activated T cells by Concanavalin A or L-PHA was also reduced in Fng tKO mice. Therefore, each Fringe contributes to T and B cell development, and Fringe is required for optimal in vitro stimulation of T and B cells.
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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) | 0.003 | 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".