MétaCan
Menu
Back to cohort
Record W2120052164 · doi:10.4049/jimmunol.1200312

Cutting Edge: miR-223 and EBV miR-BART15 Regulate the NLRP3 Inflammasome and IL-1β Production

2012· article· en· W2120052164 on OpenAlexaff
Moritz Haneklaus, Motti Gerlic, Mariola Kurowska‐Stolarska, A. Rainey, Dagmar Pich, Iain B. McInnes, Wolfgang Hammerschmidt, Luke O'neill, Seth L. Masters

Bibliographic record

VenueThe Journal of Immunology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsInstitute of Infection and ImmunityTrinity College
FundersVersus Arthritis
KeywordsInflammasomeUntranslated regionmicroRNAMicrovesiclesCell biologyThree prime untranslated regionDownregulation and upregulationInflammationEndogenyBiologyMessenger RNAChemistryImmunologyGeneBiochemistry

Abstract

fetched live from OpenAlex

Although microRNA (miRNA) regulation of TLR signaling is well established, this has not yet been observed for NLR proteins or the inflammasomes they form. We have now validated a highly conserved miR-223 target site in the NLRP3 3'-untranslated region. miR-223 expression decreases as monocytes differentiate into macrophages, whereas NLRP3 protein increases during this time. However, overexpression of miR-223 prevents accumulation of NLRP3 protein and inhibits IL-1β production from the inflammasome. Virus inhibition of the inflammasome is an emerging theme, and we have also identified an EBV miRNA that can target the miR-223 binding site in the NLRP3 3'-untranslated region. Furthermore, this virus miRNA can be secreted from infected B cells via exosomes to inhibit the NLRP3 inflammasome in noninfected cells. Therefore, we have identified both the first endogenous miRNA that limits NLRP3 inflammatory capacity during myeloid cell development and also a viral miRNA that takes advantage of this, limiting inflammation for its own purposes.

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 score0.002
Threshold uncertainty score0.007

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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

Citations451
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of ImmunologySame topicInflammasome and immune disordersFrench-language works237,207