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Record W4386933556 · doi:10.3390/biology12091259

IFNγ-Producing B Cells Play a Regulating Role in Infection-Mediated Inhibition of Allergy

2023· article· en· W4386933556 on OpenAlexafffund
Sai Qiao, Ying Peng, Chunyan Zhang, Rony Thomas, Shuhe Wang, Xi Yang

Bibliographic record

VenueBiology · 2023
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of ChinaUniversity of Manitoba
KeywordsBiologyAdoptive cell transferImmunologyImmunoglobulin EOvalbuminCytokineEosinophiliaAntibodyAllergyImmune systemT cell

Abstract

fetched live from OpenAlex

(Cm) lung infection can inhibit local eosinophilic inflammation induced by ovalbumin (OVA) through the modulation of dendritic cell (DC) and T cell responses in mice. In this study, we explored the role of B cells in the chlamydial-infection-mediated modulation of allergic responses. The results showed that adoptive transfer of B cells isolated from Cm-infected mice (Cm-B cells), unlike those from naïve mice (naïve B cells), could effectively inhibit allergic airway eosinophilia and mucus overproduction, as well as Th2 cytokine responses. In addition, total IgE/IgG1 and OVA-specific IgE/IgG1 antibodies in the serum were also decreased by the adoptive transfer of Cm-B cells. Intracellular cytokine analysis showed that B cells from Cm-infected mice produced higher levels of IFNγ than those from naïve mice. More interestingly, the inhibiting effect of adoptively transferred Cm-B cells on allergic reactions was virtually abolished by the simultaneous blockade of IFNγ using a monoclonal antibody. The results suggest that B cells modulated by chlamydial lung infection could play a regulatory role in OVA-induced acute allergic responses in the lung via the production of IFNγ. The results provide new insights into the targets related to the prevention and treatment of allergic diseases.

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 score0.756
Threshold uncertainty score0.212

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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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