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C-Terminal Domain of the Epstein-Barr Virus LMP2A Membrane Protein Contains a Clustering Signal

2001· article· en· W2112901595 on OpenAlexafffund
Liudmila Matskova, Ingemar Ernberg, Tony Pawson, Gösta Winberg

Bibliographic record

VenueJournal of Virology · 2001
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsMount Sinai Hospital
FundersCanadian Institutes of Health ResearchNational Cancer InstituteVetenskapsrådetCancerfonden
KeywordsBiologyVirusVirologyMembrane proteinCluster analysisTerminal (telecommunication)Signal peptideDomain (mathematical analysis)Protein domainIntegral membrane proteinCell biologyPeptide sequenceGeneticsMolecular biologyMembraneGene

Abstract

fetched live from OpenAlex

The latency-regulated transmembrane protein LMP2A interferes with signaling from the B-cell antigen receptor by recruiting the tyrosine kinases Lyn and Syk and by targeting them for degradation by binding the cellular E3 ubiquitin ligase AIP4. It has been hypothesized that this constitutive activity of LMP2A requires clustering in the membrane, but molecular evidence for this has been lacking. In the present study we show that LMP2A coclusters with chimeric rat CD2 transmembrane molecules carrying the 27-amino-acid (aa) intracellular C terminus of LMP2A and that this C-terminal domain fused to the glutathione-S-transferase protein associates with LMP2A in cell lysates. This molecular association requires neither the cysteine-rich region between aa 471 and 480 nor the terminal three aa 495 to 497. We also show that the juxtamembrane cysteine repeats in the LMP2A C terminus are the major targets for palmitoylation but that this acylation is not required for targeting of LMP2A to detergent-insoluble glycolipid-enriched membrane microdomains.

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 score0.003
Threshold uncertainty score0.012

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)0.0030.003

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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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
Published2001
Admission routes2
Has abstractyes

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