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Record W3026903150 · doi:10.3389/fvets.2020.00256

Protection of Cattle Elicited Using a Bivalent Lumpy Skin Disease Virus-Vectored Recombinant Rift Valley Fever Vaccine

2020· article· en· W3026903150 on OpenAlexafffund
David B. Wallace, Arshad Mather, Pravesh Kara, Leeann Naicker, Nobalanda B. Mokoena, Alri Pretorius, N. Thema, Shawn Babiuk

Bibliographic record

VenueFrontiers in Veterinary Science · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsUniversity of ManitobaCanadian Food Inspection Agency
FundersGlobal Affairs CanadaInternational Development Research Centre
KeywordsRift Valley feverVirologyBiologyRecombinant DNAVirusRecombinant virusGeneGenetics

Abstract

fetched live from OpenAlex

Lumpy skin disease and Rift Valley fever are two high-priority livestock diseases which have the potential to spread into previously free regions through animal movement and/or vectors, as well as intentional release by bioterrorists. Since the distribution range of both diseases is similar in Africa it makes sense to use a bivalent vaccine to control them. This may lead to the more consistent and sustainable use of vaccination against Rift Valley fever through a more cost-effective vaccine. In this study, a recombinant lumpy skin disease virus was constructed in which the thymidine kinase gene was used as the insertion site for the Gn and Gc protective glycoprotein genes of Rift Valley fever virus using homologous recombination. Selection markers, the enhanced green fluorescent protein and Escherichia coli guanidine phosphoribosyl transferase (gpt), were used for selection of recombinant virus and designed to allow for a second recombination event to occur upon removal of the gpt selection-pressure allowing the removal of both marker genes in the final product. This recombinant virus, LSD-RVF.mf, was selected to homogeneity, characterised and evaluated in cattle as a vaccine to show protection against both lumpy skin disease and Rift Valley fever in cattle.

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 score0.648
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.283
Teacher spread0.241 · 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

Citations39
Published2020
Admission routes2
Has abstractyes

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