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Record W2962120366 · doi:10.3390/v11070645

Vesicular Stomatitis Virus-Based Vaccines Provide Cross-Protection against Andes and Sin Nombre Viruses

2019· article· en· W2962120366 on OpenAlexafffund
Bryce M. Warner, Derek R. Stein, Rohit K. Jangra, Megan M. Slough, Patrycja Sroga, Angela Sloan, Kathy L. Frost, Stephanie A. Booth, Kartik Chandran, David Safronetz

Bibliographic record

VenueViruses · 2019
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthPublic Health AgencyPublic Health Agency of Canada
KeywordsVirologyVesicular stomatitis virusBiologyVirusVesicular StomatitisHantavirusAttenuated vaccineGeneticsVirulence

Abstract

fetched live from OpenAlex

Andes virus (ANDV) and Sin Nombre virus (SNV) are the main causative agents responsible for hantavirus cardiopulmonary syndrome (HCPS) in the Americas. HCPS is a severe respiratory disease with a high fatality rate for which there are no approved therapeutics or vaccines available. Some vaccine approaches for HCPS have been tested in preclinical models, but none have been tested in infectious models in regard to their ability to protect against multiple species of HCPS-causing viruses. Here, we utilize recombinant vesicular stomatitis virus-based (VSV) vaccines for Andes virus (ANDV) and Sin Nombre virus (SNV) and assess their ability to provide cross-protection in infectious challenge models. We show that, while both rVSVΔG/ANDVGPC and rVSVΔG/SNVGPC display attenuated growth as compared to wild type VSV, each vaccine is able to induce a cross-reactive antibody response. Both vaccines protected against both homologous and heterologous challenge with ANDV and SNV and prevented HCPS in a lethal ANDV challenge model. This study provides evidence that the development of a single vaccine against HCPS-causing hantaviruses could provide protection against multiple agents.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.817

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 head0.029
GPT teacher head0.303
Teacher spread0.274 · 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

Citations29
Published2019
Admission routes2
Has abstractyes

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