Quercetin and Resveratrol Differentially Decrease Expression of the High-Affinity IgE Receptor (FcεRI) by Human and Mouse Mast Cells
Bibliographic record
Abstract
Mast cells (MC) synthesize and store proinflammatory mediators and are centrally important in atopic diseases such as asthma and atopic dermatitis. Quercetin a and resveratrol are plant derived polyphenolic compounds with anti-inflammatory properties that inhibit MC degranulation and mediator release. However, the underlying mechanism of these inhibitory effects on MC is poorly understood and it is unclear whether this is a general effect on all MC phenotypes. We have characterized and compared the effects of quercetin with resveratrol on human (LAD2) and mouse (MC/9 and BMMC) MC mediator release, receptor expression and FcεRI signaling to better understand the mechanisms involved in quercetin and resveratrol-mediated inhibition of MC activation. Quercetin significantly decreased the expression of FcεRI by BMMC and MC/9, although the effects on MC/9 were associated with a significant reduction in cell viability. Quercetin also inhibited antigen-stimulated TNF release by BMMC. Although neither quercetin nor resveratrol significantly altered antigen-stimulated BMMC degranulation or downstream signaling events such as phosphorylation of spleen tyrosine kinase (SYK) or extracellular signal-regulated kinase 1/2 (ERK), resveratrol inhibited ERK phosphorylation and FcεRI- stimulated degranulation in LAD2. Our data suggests that quercetin and resveratrol inhibit human and mouse MC differentially and that these effects are associated with modification of FcεRI expression, signaling (phosphorylation of SYK and ERK) and mediator release.
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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) | 0.002 | 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".