SLAP negatively regulates FcɛRI receptor-mediated mast cell response in mice
Bibliographic record
Abstract
Abstract Mast cells (MCs) are key mediators of innate immune response to pathogens and allergens, etiological factors for drugs, dust and peanut-induced anaphylaxis. Degranulation of MCs in response to binding of high affinity FcɛRI receptor (IgE receptor) to allergen-induced IgE results in the release of preformed mediators including histamine, and de novo synthesis of cytokines causing hypersensitivity symptoms including anaphylaxis. Src-like adapter protein (SLAP), has been shown to regulate signaling downstream of T cell receptor (TCR), B cell receptor (BCR) and receptor tyrosine kinases (RTK) including c-Kit, FLT3 and CSF-1 via recruitment of the Cbl ubiquitin ligase. Here, we show that bone marrow-derived mast cells (BMMCs) from SLAP knockout (SLAP KO) mice displayed significantly enhanced degranulation and de novo synthesis of IL-6 but not TNFα compared to wild type (WT) BMMCs. SLAP KO BMMCs also displayed significantly reduced F-actin polymerization upon stimulation of IgE receptor in comparison to WT BMMCs. In addition, SLAP KO BMMCs maintained enhanced cell surface expression of FcɛRI receptor post stimulation suggesting reduced endocytosis/degradation. While WT and SLAP KO mice have equal numbers of MCs in ear skin, SLAP KO mice showed enhanced passive cutaneous anaphylaxis response. Thus, these results suggest that SLAP negatively regulates MC-induced anaphylaxis reaction via IgE-DNP pathway.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".