The Early Growth Response Factor-1 Is Involved in Stem Cell Factor (SCF)-induced Interleukin 13 Production by Mast Cells, but Is Dispensable for SCF-dependent Mast Cell Growth
Bibliographic record
Abstract
The stem cell factor (SCF) plays a central role in the regulation of mast cell function and growth. However, roles of transcription factors involved in these processes remain incompletely defined. The early growth response factor-1 (Egr-1) is a member of the zinc finger transcription factor family. A role for Egr-1 in SCF-induced mast cell activation and growth was investigated in mouse bone marrow-derived mast cells (BMMC). The stimulation of BMMC with SCF induced a strong expression of Egr-1 mRNA. SCF-induced Egr-1 nuclear translocation and DNA binding were demonstrated by electrophoretic mobility shift assay (EMSA) and immunofluorescence assay. SCF-induced IL-13 expression was significantly reduced at both mRNA and protein levels in Egr-1-deficient BMMC. In addition, the synergy between IgE and SCF on IL-13 and IL-4 production was reduced in Egr-1-deficient mast cells. Interestingly, Egr-1 deficiency had little effect on SCF-induced mast cell growth. SCF-induced Egr activation likely requires tyrosine phosphorylation because a tyrosine kinase inhibitor PP2 blocked SCF-induced nuclear protein binding to Egr probe as determined by EMSA. Thus, Egr-1 is required for SCF-induced IL-13 expression, but not mast cell growth. Egr-1 represents a novel mechanism for SCF-induced mast cell activation.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".