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Record W1671465655 · doi:10.4049/jimmunol.172.6.3590

Hyperproduction of Proinflammatory Cytokines by WSX-1-Deficient NKT Cells in Concanavalin A-Induced Hepatitis

2004· article· en· W1671465655 on OpenAlexaff
Atsushi Yamanaka, Shinjiro Hamano, Yoshiyuki Miyazaki, Kazunari Ishii, Atsunobu Takeda, Tak W. Mak, Kunisuke Himeno, Akihiko Yoshimura, Hiroki Yoshida

Bibliographic record

VenueThe Journal of Immunology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsProinflammatory cytokineKnockout mouseImmunologyLiver injuryTumor necrosis factor alphaInflammationConcanavalin ACytokineBiologyNatural killer T cellImmune systemReceptorT cellIn vitroEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

Administration of Con A induces liver injury that is considered to be an experimental model for human autoimmune or viral hepatitis, where immunopathology plays roles mediated by activated lymphocytes, especially NK1.1+ CD3+ NKT cells, and inflammatory cytokines, including IFN-gamma and IL-4. In the present study we investigated the role of WSX-1, a component of IL-27R, in Con A-induced hepatitis by taking advantage of WSX-1 knockout mice. WSX-1-deficient mice were more susceptible to Con A treatment than wild-type mice, showing serum alanine aminotransferase elevation and massive necrosis in the liver. Although the development of NKT cells appeared normal in WSX-1 knockout mice, purified NKT cells from the knockout mice produced more IFN-gamma and IL-4 than those from wild-type mice in response to stimulation with Con A both in vitro and in vivo. In addition, hyperproduction of proinflammatory cytokines, including IL-1, IL-6, and TNF-alpha, was observed in the knockout mice after Con A administration. These data revealed a novel role for WSX-1 as an inhibitory regulator of cytokine production and inflammation in Con A-induced hepatitis.

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 score0.018
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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

Citations83
Published2004
Admission routes1
Has abstractyes

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