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Record W2028987132 · doi:10.1139/bcb-2014-0163

Interleukin-33 promotes inflammatory cytokine production in chronic airway inflammation

2015· article· en· W2028987132 on OpenAlexvenueno aff
Jin Shang, Junling Zhao, Xiaojie Wu, Yongjian Xu, Jungang Xie

Bibliographic record

VenueBiochemistry and Cell Biology · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsnot available
Fundersnot available
KeywordsPeripheral blood mononuclear cellInflammationCytokineImmunologyCOPDMedicineInterleukin 33p38 mitogen-activated protein kinasesDownregulation and upregulationInterleukinMAPK/ERK pathwaySignal transductionBiologyCell biologyInternal medicineIn vitro

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.212
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2015
Admission routes1
Has abstractyes

Explore more

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