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Record W3157354629 · doi:10.1128/jvi.00433-21

Negeviruses Reduce Replication of Alphaviruses during Coinfection

2021· article· en· W3157354629 on OpenAlexaff
Edward I. Patterson, Tiffany F. Kautz, María Angélica Contreras-Gutiérrez, Hilda Guzmán, Robert B. Tesh, Grant L. Hughes, Naomi L. Forrester

Bibliographic record

VenueJournal of Virology · 2021
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsBrock University
FundersNational Institute of Allergy and Infectious DiseasesEconomic and Social Research CouncilBiotechnology and Biological Sciences Research CouncilNational Institutes of HealthLiverpool School of Tropical Medicine
KeywordsBiologyCoinfectionVirologyViral replicationReplication (statistics)Range (aeronautics)Virus

Abstract

fetched live from OpenAlex

Negeviruses are a group of insect-specific viruses (ISVs), viruses known to infect only insects. They have been discovered over a wide geographical and species range. Their ability to infect mosquito species that transmit dangerous arboviruses makes negeviruses a candidate for a pathogen control platform. Coinfections of mosquito cells with a negevirus and an alphavirus demonstrated that negeviruses can inhibit the replication of alphaviruses. Additionally, modifying Negev virus (NEGV) to express a fragment of an anti-CHIKV antibody further reduced the replication of CHIKV in coinfected cells. This is the first evidence to demonstrate that negeviruses can inhibit the replication of important arboviruses in mosquito cells. The ability of a modified NEGV to drive the expression of antiviral proteins also highlights a method for negeviruses to target specific pathogens and limit the incidence of vector-borne diseases.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.239

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 integrity0.0000.000
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 head0.327
Teacher spread0.308 · 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

Citations65
Published2021
Admission routes1
Has abstractyes

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