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Record W2979621346 · doi:10.1128/jvi.01220-19

Mouse Cytomegalovirus m153 Protein Stabilizes Expression of the Inhibitory NKR-P1B Ligand Clr-b

2019· article· en· W2979621346 on OpenAlexafffund
Oscar A. Aguilar, Isabella dos Santos Sampaio, Mir Munir A. Rahim, Jackeline Samaniego, Mulualem E. Tilahun, Mithunah Krishnamoorthy, Branka Popović, Marina Babić, Astrid Krmpotić, Bebhinn Treanor, David H. Margulies, David Allan, Andrew P. Makrigiannis, Stipan Jonjić, James R. Carlyle

Bibliographic record

VenueJournal of Virology · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity of OttawaUniversity of Toronto
FundersCanadian Institutes of Health ResearchNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaBurroughs Wellcome Fund
KeywordsBiologyImmune systemReceptorInnate immune systemVirologyGlycoproteinGeneVirusDownregulation and upregulationCell biologyImmunologyMolecular biologyGenetics

Abstract

fetched live from OpenAlex

Cytomegaloviruses are betaherpesviruses that in immunocompromised individuals can lead to severe pathologies. These viruses encode various gene products that serve to evade innate immune recognition. NK cells are among the first immune cells that respond to CMV infection and use germ line-encoded NK cell receptors (NKR) to distinguish healthy from virus-infected cells. One such axis that plays a critical role in NK recognition involves the inhibitory NKR-P1B receptor, which engages the host ligand Clr-b, a molecule commonly lost on stressed cells ("missing-self"). In this study, we discovered that mouse CMV utilizes the m153 glycoprotein to circumvent host-mediated Clr-b downregulation, in order to evade NK recognition. These results highlight a novel MCMV-mediated immune evasion strategy.

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 integrity0.0000.001
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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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

Citations9
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Virology→Same topicImmune Cell Function and Interaction→French-language works237,207→