Carnosic acid inhibits secretion of allergic inflammatory mediators in IgE-activated mast cells via direct regulation of Syk activation
Bibliographic record
Abstract
Mast cells are essential regulators of inflammation most recognized for their central role in allergic inflammatory disorders. Signaling via the high-affinity immunoglobulin E (IgE) receptor, FcεRI, leads to rapid degranulation of preformed granules and the sustained release of newly synthesized proinflammatory mediators. Our group recently established rosemary extract as a potent regulator of mast cell functions, attenuating MAPK and NF-κB signaling. Carnosic acid (CA)—a major polyphenolic constituent of rosemary extract—has been shown to exhibit anti-inflammatory effects in other immune cell models, but its role as a potential modulator of mast cell activation is undefined. Therefore, we sought here to determine the modulatory effects of CA in a mast cell model of allergic inflammation. We sensitized bone marrow–derived mast cells with anti-trinitrophenyl IgE and activated with allergen (TNP-BSA) under stem cell factor potentiation, in addition to treatment with CA. Our results indicate that CA significantly inhibits allergen-induced early phase responses including Ca 2+ mobilization, ROS production, and subsequent degranulation. We also show CA treatment reduced late phase responses, including the release of all cytokines and chemokines examined following IgE stimulation and corresponding gene expression excepting that of CCL2. Importantly, we determined that CA mediates its inhibitory effects through modulation of tyrosine kinase Syk and downstream effectors TAK1 (Ser412) and Akt (Ser473) as well as NFκB signaling, while phosphorylation of FcεRI (γ chain) and MAPK proteins remained unaltered. These novel findings establish CA as a potent modulator of mast cell activation, warranting further investigation as a putative anti-allergy therapeutic.
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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".