Potentiation of NF‐κB‐dependent transcription and inflammatory mediator release by histamine in human airway epithelial cells
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In asthma, histamine contributes to bronchoconstriction, vasodilatation and oedema, and is associated with the late phase response. The current study investigates possible inflammatory effects of histamine acting on nuclear factor kappaB (NF-kappaB)-dependent transcription and cytokine release. EXPERIMENTAL APPROACH: Using BEAS-2B bronchial epithelial cells, NF-kappaB-dependent transcription and both release and mRNA expression of IL-6 and IL-8 were examined by reporter assay, ELISA and quantitative RT-PCR. Histamine receptors were detected using qualitative RT-PCR and function examined using selective agonists and antagonists. KEY RESULTS: Addition of histamine to TNFalpha-stimulated BEAS-2B cells maximally potentiated NF-kappaB-dependent transcription 1.8 fold, whereas IL-6 and IL-8 protein release were enhanced 7.3- and 2.7-fold respectively. These responses were, in part, NF-kappaB-dependent and were associated with 2.6- and 1.7-fold enhancements of IL-6 and IL-8 mRNA expression. The H(1) receptor antagonist, mepyramine, caused a rightward shift in the concentration-response curves of TNFalpha-induced NF-kappaB-dependent transcription (pA(2)=9.91) and release of IL-6 (pA(2)=8.78) and IL-8 (pA(2)=8.99). Antagonists of histamine H(2), H(3) and H(4) receptors were without effect. Similarly, H(3) and H(4) receptor agonists did not affect TNFalpha-induced NF-kappaB-dependent transcription, or IL-6 and IL-8 release at concentrations below 10 microM. The anti-inflammatory glucocorticoid, dexamethasone, inhibited the histamine enhanced NF-kappaB-dependent transcription and IL-6 and IL-8 release. CONCLUSIONS AND IMPLICATIONS: Potentiation of NF-kappaB-dependent transcription and inflammatory cytokine release by histamine predominantly involves receptors of the H(1) receptor subtype. These data support an anti-inflammatory role for H(1) receptor antagonists by preventing the transcription and release of pro-inflammatory cytokines.
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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 | 0.001 | 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) | 0.001 | 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".