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IL-10 deficiency prevents IL-5 overproduction and eosinophilic inflammation in a murine model of asthma-like reaction

2000· article· en· W1968776503 on OpenAlexaff
Xi Yang, Shuhe Wang, Yijun Fan, Xiaobing Han

Bibliographic record

VenueEuropean Journal of Immunology · 2000
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsImmunologyOvalbuminInflammationMucusCytokineImmunoglobulin EBiologyInterleukin 5EosinophilicInterleukin 13SensitizationInterleukin 4Knockout mouseAsthmaSecretionInterleukinImmune systemEndocrinologyAntibodyGene

Abstract

fetched live from OpenAlex

Eosinophilic inflammation and bronchial mucus secretion are among the characteristic pathological changes in asthmatic reaction, which is mediated by Th2 type responses. Although it belongs to Th2 cytokines especially in the mouse, IL-10 is often considered an inhibitory cytokine for both Th1 and Th2 cells. In the present study, using a murine asthma model induced by ovalbumin (OVA), we demonstrated that endogenous IL-10 is critical for the development of asthma-like responses. Specifically, in comparison with wild-type controls, IL-10 gene knockout (KO) mice showed significantly reduced IL-5 production, eosinophilic inflammation and mucus production without notable changes in IL-4 and IgE responses following i. p. sensitization and subsequent intranasal challenge with OVA. In addition, Th1-related cytokine (IFN-gamma and IL-12) production in IL-10 KO mice was significantly higher than that in wild-type mice. The results suggest that endogenous IL-10 plays an important role in promoting pulmonary eosinophilic inflammatory reaction and mucus production during asthmatic reaction. The data also argue that IL-10 may be more influential in the development of IL-5-producing Th2 cells which differ from typical Th2 cells producing both IL-4 and IL-5.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.321

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 integrity0.0000.000
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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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 designObservational
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

Citations85
Published2000
Admission routes1
Has abstractyes

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