Calpain-1 Contributes to IgE-Mediated Mast Cell Activation
Bibliographic record
Abstract
Mast cells play a central role in allergy through secretion of both preformed and newly synthesized mediators. Mast cell mediator secretion is controlled by a complex network of signaling events. Despite intensive studies, signaling pathways in the regulation of mast cell mediator secretion remain incompletely defined. In this study, we examined the role of calpain in IgE-dependent mast cell activation. IgE-mediated activation of mouse bone marrow-derived mast cells enhanced calpain activity. Inhibition of calpain activity by a number of calpain inhibitors reduced IgE-mediated mast cell degranulation both in vitro and in vivo. Calpain inhibitors blocked IgE-mediated TNF and IL-6 production in vitro and reduced late-phase allergic response in vivo. Importantly, mouse calpain-1 null bone marrow-derived mast cells showed reduced IgE-mediated mast cell degranulation in vitro and in vivo, diminished cytokine and chemokine production in vitro, and impaired late-phase allergic response in vivo. Further studies revealed that calpain-1 deficiency led to specific attenuation of IκB-NF-κB pathway and IKK-SNAP23 pathway, whereas calcium flux, MAPK, Akt, and NFAT pathway proceed normally in IgE-activated calpain-1 null mast cells. Thus, calpain-1 is identified as a novel regulator in IgE-mediated mast cell activation and could serve as a potential therapeutic target for the management of allergic inflammation.
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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 | 0.001 | 0.001 |
| 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".