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Record W2898324345 · doi:10.1038/s41598-018-34484-7

The interaction between the Nipah virus nucleocapsid protein and phosphoprotein regulates virus replication

2018· article· en· W2898324345 on OpenAlexaff
Charlene Ranadheera, Roxanne Proulx, Mark Chaiyakul, Shane Jones, Allen Grolla, Anders Leung, John D. Rutherford, Darwyn Kobasa, Michael Carpenter, Markus Czub

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsUniversity of CalgaryUniversity of ManitobaPublic Health Agency of Canada
Fundersnot available
KeywordsPhosphoproteinVirologyViral replicationBiologyPolymeraseViral structural proteinVirusViral entryViral proteinTranscription (linguistics)GeneGenetics

Abstract

fetched live from OpenAlex

Continued outbreaks of Henipaviruses in South Asia and Australia cause severe and lethal disease in both humans and animals. Together, with evidence of human to human transmission for Nipah virus and the lack of preventative or therapeutic measures, its threat to cause a widespread outbreak and its potential for weaponization has increased. In this study we demonstrate how overexpression of the Nipah virus nucleocapsid protein regulates viral polymerase activity and viral RNA production. By overexpressing the Nipah virus nucleocapsid protein in trans viral transcription was inhibited; however, an increase in viral genome synthesis was observed. Together, the bias of polymerase activity towards genome production led to the severe inhibition of viral progeny. We identified two domains within the nucleocapsid protein, which were each independently capable of binding the viral phosphoprotein. Evident by our data, we propose that the nucleocapsid protein's ability to interact with the phosphoprotein of the polymerase complex causes a change in polymerase activity and subsequent deficiency in viral replication. This study not only provides insights into the dynamics of Henipavirus RNA synthesis and replication, but also provides insight into potential targets for antiviral drug development.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.122
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.297
Teacher spread0.277 · 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 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

Citations35
Published2018
Admission routes1
Has abstractyes

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