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Protective Role for Interferon-β in Coxsackievirus B3 Infection

2004· article· en· W2113080976 on OpenAlexaff
Raj Deonarain, Dante Cerullo, Koichi Fuse, Peter P. Liu, Eleanor N. Fish

Bibliographic record

VenueCirculation · 2004
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsHeart and Stroke Foundation
Fundersnot available
KeywordsCoxsackievirusMyocarditisMedicineInterferonImmunologyImmune systemInnate immune systemDownregulation and upregulationVirusVirologyBETA (programming language)GeneBiologyEnterovirus

Abstract

fetched live from OpenAlex

BACKGROUND: Coxsackievirus-induced myocarditis can be a serious cause of heart failure. In the absence of a specific antiviral therapy, modulating the host immune response may be protective. Interferons (IFNs)-alpha and -beta perform a fundamental role in innate and adaptive antiviral responses, thereby presenting as candidate therapeutics for coxsackievirus infections. METHODS AND RESULTS: To examine the contribution of IFN-beta in protection from coxsackievirus B3 (CVB3) infection, mice lacking the IFN-beta gene were infected with 10(3) plaque-forming units of CVB3. In contrast to wild-type mice that exhibit an intact IFN-beta response, we observed increased susceptibility to infection (70% mortality), a downregulation of IFN-stimulated gene targets (2'-5' oligoadenylate synthetase, serine/threonine protein kinase, the GTPase Mx), and cardiomyocyte breakdown and disruption in the IFN-beta-/- mice. CONCLUSIONS: Viewed together, these results clearly demonstrate that IFN-beta is important in mediating protection against CVB3-induced myocarditis.

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 score0.004

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 head0.037
GPT teacher head0.340
Teacher spread0.303 · 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

Citations159
Published2004
Admission routes1
Has abstractyes

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