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Record W1518320249 · doi:10.1002/eji.201344206

Inhibition of STAT6 during vaccination with formalin‐inactivated RSV prevents induction of Th2‐cell‐biased airway disease

2014· article· en· W1518320249 on OpenAlexafffund
Bharat T. Srinivasa, Elizabeth D. Fixman, Brian J. Ward

Bibliographic record

VenueEuropean Journal of Immunology · 2014
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsMcGill University Health CentreMontreal General Hospital
FundersCanadian Institutes of Health ResearchMcGill University Health CentreNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsVaccinationImmunologyNasal administrationSTAT6BiologyImmune systemCD8T cellAntigenVirologyInterleukin 4

Abstract

fetched live from OpenAlex

The pattern of immune response to a vaccine antigen can influence both efficacy and adverse events. Th2-cell-deviated responses have been implicated in both human and murine susceptibility to enhanced disease following formalin-inactivated (FI) vaccines for measles and RSV. In this study, we used the Th2-cell-deviated murine model of FI-RSV vaccination to test the ability of a dominant negative, cell-penetrating peptide inhibitor of STAT6 (STAT6 inhibitory peptide (IP)) to modulate the vaccine-induced predisposition to exaggerated inflammation during later RSV infection. Intranasal delivery of STAT6-IP in BALB/c mice at the time of distal intramuscular FI-RSV vaccination (Early Intervention) markedly decreased vaccine-enhanced, Th2-cell-dependent pathology upon subsequent RSV challenge. Administration of the STAT6-IP at the time of RSV challenge (Late Intervention) had no effect. Following RSV challenge, the STAT6-IP-treated mice in the Early Intervention group had lower airway eosinophils, increased lung IFN-γ levels, as well as increased IFN-γ-secreting CD4(+) and CD8(+) cells in the lungs. Our findings demonstrate the feasibility of targeting intracellular signaling pathways as a new way to modulate vaccine-induced responses.

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)0.001
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 score0.367
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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

Citations9
Published2014
Admission routes2
Has abstractyes

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