Egr1-Rcan1 axis serves as a molecular switch from activation to inhibition in IgE-mediated signalling (139.3)
Bibliographic record
Abstract
Abstract Mast cells play a central role in allergy. Aggregation of FcεRI activates a cascade of signaling events leading to mast cell activation. Subsequently, inhibitory signals are switched on for turning off activated signals. Here we identified that Rcan1 serves as a negative regulator for turning off FcεRI-mediated mast cell activation. FcεRI-induced Rcan1 expression was identified by suppression subtractive hybridization and verified by real-time quantitative PCR and Western blotting. Deficiency of Rcan1 led to increased calcineurin activity, increased NFAT and NF-κB activation, increased cytokine production and enhanced IgE-mediated late phase cutaneous reactions. Forced expression of Rcan1 in wild type or Rcan1 deficient mast cells reduced FcεRI-mediated cytokine production in vitro. Rcan1 deficiency also led to increased FcεRI-mediated mast cell degranulation and enhanced passive cutaneous anaphylaxis. Analysis of the Rcan1 promoter identified a functional Egr1 binding site. Rcan1 expression is preceded by Egr1 expression. Egr1 is a positive regulator of FcεRI-induced cytokine production. Biochemical and genetic evidence suggested that Egr1 controls Rcan1 expression. Our results identified Rcan1 as a novel inhibitory signal in FcεRI-induced mast cell activation and established a new link of Egr1 and Rcan1 in FcεRI signaling.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".