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Record W3134501918 · doi:10.1128/jvi.02006-20

The Reovirus μ2 C-Terminal Loop Inversely Regulates NTPase and Transcription Functions versus Binding to Factory-Forming μNS and Promotes Replication in Tumorigenic Cells

2021· article· en· W3134501918 on OpenAlexafffund
Wan Kong Yip, Francisca Cristi, Georgi Trifonov, Nashae Narayan, Mark Kubanski, Maya Shmulevitz

Bibliographic record

VenueJournal of Virology · 2021
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of Alberta
FundersFaculty of Graduate Studies and Research, University of AlbertaCanadian Cancer Society Research InstituteCanada Research ChairsCanada Foundation for InnovationGovernment of CanadaLi Ka Shing Institute of Virology, University of AlbertaFaculty of Medicine and Dentistry, University of AlbertaAlberta Innovates - Health SolutionsCanadian Institutes of Health ResearchCancer Research SocietyUniversity of AlbertaCancer Research Institute
KeywordsBiologyVirologyViral replicationTranscription (linguistics)Replication (statistics)VirusCell biologyOncolytic virusMutationReoviridaeMolecular biologyGeneticsGene

Abstract

fetched live from OpenAlex

Reovirus is a model system for understanding virus replication but also a clinically relevant virus for cancer therapy. We identified the first mutation that increases reovirus infection in tumorigenic cells by enhancing post-entry stages of reovirus replication. The mutation is in a previously uncharacterized c-terminal region of the M1-derived μ2 protein, which we demonstrated affects multiple functions of μ2; NTPase, RNA synthesis, inhibition of antiviral immune response and association with the virus replication factory-forming μNS protein. These findings promote a mechanistic understanding of viral protein functions. In the future, the benefits of μ2 mutations may be useful for enhancing reovirus potency in tumors.

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)0.0000.000
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 head0.046
GPT teacher head0.326
Teacher spread0.280 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

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