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Record W2138298422 · doi:10.4049/jimmunol.172.10.6202

Toll-Like Receptor 4 Dependence of Innate and Adaptive Immunity to <i>Salmonella</i> : Importance of the Kupffer Cell Network

2004· article· en· W2138298422 on OpenAlexaff
Andrés Vázquez‐Torres, Bruce A. Vallance, Molly A. Bergman, B. Brett Finlay, Brad T. Cookson, Jessica Jones‐Carson, Ferric C. Fang

Bibliographic record

VenueThe Journal of Immunology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of British Columbia
FundersNational Center for Research ResourcesNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsTLR4Innate immune systemBiologyAcquired immune systemSalmonellaToll-like receptorImmune systemReceptorChemokineMicrobiologyImmunologyBacteriaCell biologyGenetics

Abstract

fetched live from OpenAlex

Mammalian cells recognize LPS from Gram-negative bacteria via the Toll-like receptor 4 (TLR4) complex. During experimental Salmonella infection, C3H/HeJ mice carrying a dominant-negative mutation in TLR4 exhibited delayed chemokine production, impaired NO generation, and attenuated cellular immune responses. However, dramatically enhanced bacterial growth within the Kupffer cell network before the recruitment of inflammatory cells appeared to be primarily responsible for the early demise of Salmonella-infected TLR4-deficient mice. LPS-TLR4 signaling plays an essential role in the generation of both innate and adaptive immune responses throughout the course of infection with Gram-negative bacteria. Alternative pattern-recognition receptors cannot completely compensate for the loss of TLR4, and compensation occurs at the expense of an increased microbial burden.

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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

Citations173
Published2004
Admission routes1
Has abstractyes

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