Primary Human Airway Epithelial Cell-Dependent Inhibition of Human Lung Mast Cell Degranulation
Bibliographic record
Abstract
INTRODUCTION: Chronic mast cell activation is a characteristic feature of asthma. BEAS-2B human airway epithelial cells (AEC) profoundly inhibit both constitutive and IgE-dependent human lung mast cell (HLMC) histamine release. The aim of this study was to examine the regulation of HLMC degranulation by primary AEC from healthy and asthmatic subjects, and investigate further the inhibitory mechanism. METHODS: HLMC were co-cultured with both BEAS-2B and primary AEC grown as monolayers or air-liquid interface (ALI) cultures. RESULTS: Both constitutive and IgE-dependent HLMC histamine release were attenuated by BEAS-2B, primary AEC monolayers and ALI cultures. This occurred in the absence of HLMC-AEC contact indicating the presence of a soluble factor. Unlike healthy ALI AEC, asthmatic ALI-AEC did not significantly reduce constitutive histamine release. AEC inhibitory activity was transferable in primary AEC monolayer supernatant, but less active than with Transwell co-culture, suggesting that the inhibitory factor was labile. The AEC inhibitory effects were attenuated by both AEC wounding and pertussis toxin, indicating the involvement of a G(0)/G(i) receptor coupled mechanism. Solid phase extraction of lipids (<10 kDa) removed the AEC inhibitory activity. The lipid derivatives resolving D1 and D2 and lipoxin A(4) attenuated HLMC histamine release in a dose-dependent fashion but were not detectable in co-culture supernatants. CONCLUSIONS: Primary AEC suppress HLMC constitutive and IgE-dependent histamine secretion through the release of a soluble, labile lipid mediator(s) that signals through the G(0)/G(i) receptor coupled mechanism. Manipulation of this interaction may have a significant therapeutic role in asthma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".