The Bcl10–Malt1 complex segregates FcεRI-mediated nuclear factor κB activation and cytokine production from mast cell degranulation
Bibliographic record
Abstract
Mast cells are pivotal effector cells in IgE-mediated allergic inflammatory diseases. Central for mast cell activation are signals from the IgE receptor FcepsilonRI, which induce cell degranulation with the release of preformed mediators and de novo synthesis of proinflammatory leukotrienes and cytokines. How these individual mast cell responses are differentially controlled is still unresolved. We identify B cell lymphoma 10 (Bcl10) and mucosa-associated lymphoid tissue 1 (Malt1) as novel key regulators of mast cell signaling. Mice deficient for either protein display severely impaired IgE-dependent late phase anaphylactic reactions. Mast cells from these animals neither activate nuclear factor kappaB (NF-kappaB) nor produce tumor necrosis factor alpha or interleukin 6 upon FcepsilonRI ligation even though proximal signaling, degranulation, and leukotriene secretion are normal. Thus, Bcl10 and Malt1 are essential positive mediators of FcepsilonRI-dependent mast cell activation that selectively uncouple NF-kappaB-induced proinflammatory cytokine production from degranulation and leukotriene synthesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".