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Helminth infection inhibits airway allergic reaction and dendritic cells are involved in the modulation process

2009· article· en· W1842663070 on OpenAlexaff
P. Liu, J. Li, Xi Yang, Yujun Shen, Y.Y.J. Zhu, S. Wang, Zhihai Wu, Xin Liu, Gary An, Wei Ji, Wei Gao

Bibliographic record

VenueParasite Immunology · 2009
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Manitoba
FundersNational Natural Science Foundation of China
KeywordsBiologyImmunologyHelminthsAirwayProcess (computing)Hygiene hypothesisHelminthiasisImmune systemMedicine

Abstract

fetched live from OpenAlex

Several previous studies have demonstrated that some helminth infections can inhibit allergic reactions, but the examination on the effect of live Schistosoma japonicum (SJ) infection on allergic inflammation remains limited. The aim of this study was to examine the effect and mechanism of chronic SJ infection on airway allergic inflammation in a murine model. The data showed that chronic SJ infection suppressed airway eosinophilia, mucus production and antigen-specific IgE responses induced by ovalbumin (OVA) sensitization and challenge. Cytokine production analysis showed that chronic SJ infection reduced allergen-driven interleukin (IL)-4 and IL-5 production, but had no significant effect on IFN-gamma production. More importantly, we found that the adoptive transfer of dendritic cells (DCs) from SJ-infected mice dramatically decreased airway allergic inflammation in the recipients, which was associated with significant decrease of IL-4/IL-5 production and increase of IL-10 production. The results suggest that SJ infection may inhibit the development of allergy and that DCs may be involved in the process of helminth infection-mediated modulation of allergic inflammation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.279
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2009
Admission routes1
Has abstractyes

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