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Record W2886478099 · doi:10.1038/s41467-018-05480-2

A stochastic assembly model for Nipah virus revealed by super-resolution microscopy

2018· article· en· W2886478099 on OpenAlexafffund
Qian Liu, Lei Chen, Hector C. Aguilar, Keng C. Chou

Bibliographic record

VenueNature Communications · 2018
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaIcahn School of Medicine at Mount Sinai
KeywordsGlycoproteinVirusViral envelopeMembraneLipid bilayer fusionViral matrix proteinBiophysicsVirologyCell biologyChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Understanding virus assembly mechanisms is important for developing therapeutic interventions. Nipah virus (NiV) is of interest because of its high mortality rate and efficient human-human transmissions. The current model for most enveloped viruses suggests that matrix proteins (M) recruit attachment glycoproteins (G) and fusion glycoproteins (F) to the assembly site at the plasma membrane. Here we report an assembly model that differs in many aspects from the current one. Examining NiV proteins on the cell plasma membrane using super-resolution microscopy reveals that clusters of F and G are randomly distributed on the plasma membrane regardless of the presence or absence of M. Our data suggests a model in which the M molecules assemble at the plasma membrane to form virus-like particles (VLPs), while the incorporation of F and G into the nascent VLPs is stochastic.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.037
GPT teacher head0.381
Teacher spread0.343 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations37
Published2018
Admission routes2
Has abstractyes

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