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Record W4225391816 · doi:10.1038/s42003-022-03367-z

IL-25 blockade augments antiviral immunity during respiratory virus infection

2022· article· en· W4225391816 on OpenAlexaff
Teresa C. Williams, Su-Ling Loo, Kristy Nichol, Andrew T. Reid, Punnam Chander Veerati, Camille Esneau, Peter Wark, Christopher Grainge, Darryl A. Knight, Thomas L. Vincent, Crystal Lyles Jackson, K Alton, Richard A. Shimkets, Jason Girkin, Nathan W. Bartlett

Bibliographic record

VenueCommunications Biology · 2022
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of British ColumbiaProvidence Health Care Research InstituteProvidence Health Care
Fundersnot available
KeywordsImmunologyInnate immune systemRhinovirusImmunityImmune systemBiologyVirusCytokineVirology

Abstract

fetched live from OpenAlex

IL-25 is implicated in the pathogenesis of viral asthma exacerbations. However, the effect of IL-25 on antiviral immunity has yet to be elucidated. We observed abundant expression and colocalization of IL-25 and IL-25 receptor at the apical surface of uninfected airway epithelial cells and rhinovirus infection increased IL-25 expression. Analysis of immune transcriptome of rhinovirus-infected differentiated asthmatic bronchial epithelial cells (BECs) treated with an anti-IL-25 monoclonal antibody (LNR125) revealed a re-calibrated response defined by increased type I/III IFN and reduced expression of type-2 immune genes CCL26, IL1RL1 and IL-25 receptor. LNR125 treatment also increased type I/III IFN expression by coronavirus infected BECs. Exogenous IL-25 treatment increased viral load with suppressed innate immunity. In vivo LNR125 treatment reduced IL-25/type 2 cytokine expression and increased IFN-β expression and reduced lung viral load. We define a new immune-regulatory role for IL-25 that directly inhibits virus induced airway epithelial cell innate anti-viral immunity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 integrity0.0000.001
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 head0.041
GPT teacher head0.336
Teacher spread0.295 · 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 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

Citations30
Published2022
Admission routes1
Has abstractyes

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