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Record W2896579627 · doi:10.1128/jvi.01285-18

Human MxB Inhibits the Replication of Hepatitis C Virus

2018· article· en· W2896579627 on OpenAlexafffund
Dongrong Yi, Ni An, Zhenlong Liu, Fengwen Xu, Kavita Raniga, Quanjie Li, Rui Zhou, Jing Wang, Yongxin Zhang, Jinming Zhou, Leiliang Zhang, Jing An, Cheng‐Feng Qin, Fei Guo, Xiaoyu Li, Chen Liang, Shan Cen

Bibliographic record

VenueJournal of Virology · 2018
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsJewish General Hospital
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchChinese Academy of Medical SciencesNational Natural Science Foundation of ChinaGovernment of Canada
KeywordsBiologyVirologyNS5ACypaFlaviviridaeViral replicationVirusHepatitis C virusDengue virusDengue feverInterferonHost factorHepacivirus

Abstract

fetched live from OpenAlex

Viruses of the Flaviviridae family cause major illness and death around the world and thus pose a great threat to human health. Here we show that IFN-inducible MxB restricts several members of the Flaviviridae , including HCV, Japanese encephalitis virus, and dengue virus. This finding not only suggests an active role of MxB in combating these major pathogenic human viruses but also significantly expands the antiviral spectrum of MxB. Our study further strengthens the link between virus dependence on CypA and susceptibility to MxB restriction and also suggests that MxB may employ a common mechanism to inhibit different viruses. Elucidating the antiviral functions of MxB advances our understanding of IFN-mediated host antiviral defense and may open new avenues to the development of novel antiviral therapeutics.

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 score0.002
Threshold uncertainty score0.008

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)0.0020.000

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 head0.045
GPT teacher head0.391
Teacher spread0.345 · 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

Citations54
Published2018
Admission routes2
Has abstractyes

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