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Fusogenic Reoviruses and Their Fusion-Associated Small Transmembrane (FAST) Proteins

2019· review· en· W2956367114 on OpenAlexafffund
Roy Duncan

Bibliographic record

VenueAnnual Review of Virology · 2019
Typereview
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyFusion mechanismTransmembrane proteinLipid bilayer fusionMembrane proteinViral envelopeCell biologyTransmembrane domainViral entryEffectorFusion proteinViral replicationVirusVirologyGeneticsMembraneGene

Abstract

fetched live from OpenAlex

With no limiting membrane surrounding virions, nonenveloped viruses have no need for membrane fusion to gain access to intracellular replication compartments. Consequently, nonenveloped viruses do not encode membrane fusion proteins. The only exception to this dogma is the fusogenic reoviruses that encode fusion-associated small transmembrane (FAST) proteins that induce syncytium formation. FAST proteins are the smallest viral membrane fusion proteins and, unlike their enveloped virus counterparts, are nonstructural proteins that evolved specifically to induce cell-to-cell, not virus-cell, membrane fusion. This distinct evolutionary imperative is reflected in structural and functional features that distinguish this singular family of viral fusogens from all other protein fusogens. These rudimentary fusogens comprise specific combinations of different membrane effector motifs assembled into small, modular membrane fusogens. FAST proteins offer a minimalist model to better understand the ubiquitous process of protein-mediated membrane fusion and to reveal novel mechanisms of nonenveloped virus dissemination that contribute to virulence.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.064
GPT teacher head0.371
Teacher spread0.307 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations63
Published2019
Admission routes2
Has abstractyes

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