Attenuation of allergen-mediated mast cell activation by rosemary extract (<i>Rosmarinus officinalis</i>L.)
Bibliographic record
Abstract
Mast cells are immune sentinels and a driving force in both normal and pathological contexts of inflammation, with a prominent role in allergic hypersensitivities. Crosslinking of FcεRI by allergen-bound IgE Abs leads to mast cell degranulation, resulting in an early-phase response and release of newly synthesized pro-inflammatory mediators in the late-phase. The MAPK and NF-κB pathways are established as critical intracellular mechanisms directing mast cell-induced inflammation. Rosemary extract (RE) has been shown to modulate the MAPK and NF-κB pathways in other cellular contexts in vitro and in vivo. However, the effect of RE on mast cell activation has not been explored, and thus we aim to evaluate the potential of RE in modulating mast cell activation and FcεRI/c-kit signaling, potentially via these key pathways. Primary murine mast cells were sensitized with anti-TNP IgE and stimulated with cognate allergen (TNP-BSA) under stem cell factor (SCF) potentiation while treated with 0-25 µg/ml RE. RE treatment inhibited phosphorylation of p38 and JNK MAPKs while also impairing NF-кB transcription factor activity. Gene expression and mediator secretion analysis showed that RE treatment decreased IL-6, TNF, IL-13, CCL1, and CCL3, but major component polyphenols do not contribute to these effects. Importantly, RE treatment significantly inhibited early phase mast cell degranulation (down to 15% of control), with carnosic acid and carnosol contributing. These findings indicate that RE is capable of modulating mast cell functional outcomes and that further investigation of the underlying mechanisms and its potential therapeutic properties in allergic inflammatory conditions is warranted.
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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) | 0.001 | 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) | 0.001 | 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 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".