Interleukin-33 promotes inflammatory cytokine production in chronic airway inflammation
Bibliographic record
Abstract
Interleukin (IL)-33, belonging to the IL-1 family, is a novel cytokine that plays an important role in several chronic inflammatory diseases. Its role in chronic airway inflammation that develops into COPD is widely unknown. To determine this, we identified the expression of IL-33 in human bronchial epithelial layer and detected the inflammatory effects of IL-33 stimulation and the relative signaling pathways in human bronchial epithelial (HBE) cells and peripheral blood mononuclear cells (PBMCs), respectively. In this study, the expression of IL-33 in human bronchial epithelial layer was upregulated in COPD patients compared with normal controls. The expressions of IL-6 and IL-8 were also increased in both HBE cells and PBMCs, stimulated by IL-33 alone or combining the cigarette smoke extract (CSE). And the increased expressions could be partially blocked by ST2-Fc and IL-1RacP-Fc in both HBE cells and PBMCs. The p42/p44 ERK inhibitor in HBE cells and the p38 MAPK inhibitor in PBMCs exerted similar effects. Our data showed that IL-33 could induce and enhance the expression of IL-6 and IL-8 in HBE cells and PBMCs of COPD patients via ST2/IL-1RacP pathway and MAPKs pathway. Thus, the IL-33 is a promoter of chronic airway inflammation that contributes to COPD development.
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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) | 0.000 | 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 | 0.001 |
| 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 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".