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Record W2094745777 · doi:10.1074/jbc.m113.519934

Mitogen-activated Protein Kinase-mediated Licensing of Interferon Regulatory Factor 3/7 Reinforces the Cell Response to Virus

2013· article· en· W2094745777 on OpenAlexfundno aff
Sonja Schmid, David Sachs, Benjamin R. tenOever

Bibliographic record

VenueJournal of Biological Chemistry · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesU.S. Public Health ServiceMcGill UniversityNational Institutes of HealthThomas Jefferson University
KeywordsInterferonProtein kinase AProtein kinase RMitogen-activated protein kinaseCell biologyInterferon regulatory factorsKinaseBiologyVirologyMitogen-activated protein kinase kinaseImmune systemImmunologyInnate immune system

Abstract

fetched live from OpenAlex

The induction of the intrinsic antiviral defense in mammals relies on the accumulation of foreign genetic material. As such, complete engagement of this response is limited to replication-competent viruses. Interferon regulatory factors (IRFs) are mediators of this defense with shared enhancer elements but display a spectrum of transcriptional potential. Here we describe a mechanism designed to enhance this response should a pathogen not be successfully inhibited. We find that activation of IRF7 results in the induction of MAP3K8 and restructuring of the antiviral transcriptome. MAP3K8 mediates the phosphorylation and repression of IRF3 homodimers to promote greater transcriptional activity through utilization of IRF3:IRF7 heterodimers. Among the genes influenced by the MAP3K8/IRF7 signaling axis are members of the SP100 gene family that serve as general transcriptional enhancers of the antiviral defense. We propose that this feed forward loop serves to reinforce the cellular response and is reserved for imminent threats to the host.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.009
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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.

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

Citations27
Published2013
Admission routes1
Has abstractyes

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