MétaCan
Menu
Back to cohort
Record W2001809367 · doi:10.1002/eji.200737429

IRAK‐4 kinase activity is required for IRAK‐4‐dependent innate and adaptive immune responses

2008· article· en· W2001809367 on OpenAlexaff
Elizabeth Lye, Salim Dhanji, Thomas Calzascia, Alisha R. Elford, Pamela S. Ohashi

Bibliographic record

VenueEuropean Journal of Immunology · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsBiologyInnate immune systemImmune systemKinaseTLR4Acquired immune systemLipopolysaccharideCell biologyImmunology

Abstract

fetched live from OpenAlex

Interleukin-1 receptor-associated kinase (IRAK)-4 is a serine-threonine kinase that plays an important role in innate and adaptive immune responses. While the requirement of IRAK-4 kinase activity has been studied in the context of IL-1R signaling, it is not clear whether IRAK-4 requires its kinase function for all of its roles in the immune system. IRAK-4 kinase-dead knock-in (IRAK-4KD/KD) mice were generated to further elucidate whether IRAK-4 kinase activity is required for IRAK-4 to induce cytokine production. IRAK-4KD/KD mice were impaired in their ability to produce cytokines in response to in vivo challenge with lipopolysaccharide (LPS), a potent TLR4 ligand. Cytokine production was also reduced in macrophages and dendritic cells from IRAK-4KD/KD mice in response to LPS and other TLR ligands. In addition, adaptive immune responses were impaired in IRAK-4KD/KD mice. Although in vitro T cell proliferation in response to TCR activation was unaffected in IRAK-4-deficient mice, in vivo T cell responses to lymphocytic choriomeningitits virus infection were significantly impaired in IRAK-4-knockout mice or mice expressing the kinase-dead mutant of IRAK-4. Collectively, these results indicate that IRAK-4 kinase activity is required for IRAK-4-dependent signaling in innate and adaptive 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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.247
Teacher spread0.217 · 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

Citations42
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of ImmunologySame topicImmune Response and InflammationFrench-language works237,207