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Record W1486935504 · doi:10.4049/jimmunol.1302392

TRIL Is Involved in Cytokine Production in the Brain following <i>Escherichia coli</i> Infection

2014· article· en· W1486935504 on OpenAlexaff
Paulina Wochal, Vijay Rathinam, Aisling Dunne, Thaddeus Carlson, Wen Kuang, Katherine J. Seidl, J. Perry Hall, Lih‐Ling Lin, Mary Collins, Stefan Schattgen, Christopher R. MacKay, Caio T. Fagundes, Susan P. Carpenter, Katherine A. Fitzgerald, Luke O'neill

Bibliographic record

VenueThe Journal of Immunology · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsTrinity College
FundersNational Institute of Allergy and Infectious Diseases
KeywordsTLR4TLR3ChemokineInnate immune systemProinflammatory cytokineBiologyCytokineImmune systemEscherichia coli infectionEscherichia coliImmunologyIn vivoCell biologyMediatorInflammationToll-like receptorGeneBiochemistry

Abstract

fetched live from OpenAlex

TLR4 interactor with leucine-rich repeats (TRIL) is a brain-enriched accessory protein that is important in TLR3 and TLR4 signaling. In this study, we generated Tril(-/-) mice and examined TLR responses in vitro and in vivo. We found a role for TRIL in both TLR4 and TLR3 signaling in mixed glial cells, consistent with the high level of expression of TRIL in these cells. We also found that TRIL is a modulator of the innate immune response to LPS challenge and Escherichia coli infection in vivo. Tril(-/-) mice produce lower levels of multiple proinflammatory cytokines and chemokines specifically within the brain after E. coli and LPS challenge. Collectively, these data uncover TRIL as a mediator of innate immune responses within the brain, where it enhances neuronal cytokine responses to infection.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.235
Teacher spread0.224 · 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

Citations34
Published2014
Admission routes1
Has abstractyes

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