MétaCan
Menu
Back to cohort

Genetic Variability of Bovine Viral Diarrhea Virus and Evidence for a Possible Genetic Bottleneck during Vertical Transmission in Persistently Infected Cattle

2015· article· en· W763178848 on OpenAlexafffund
Natalie Rose Dow, Adam Chernick, Karin Orsel, Guido van Marle, Frank van der Meer

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversity of Calgary
FundersAlberta Livestock and Meat AgencyUniversity of Calgary
KeywordsBiologyViral quasispeciesVirologyVirusPestivirusViral evolutionTransmission (telecommunications)FlaviviridaeGenetic variabilityCattle DiseasesGeneticsViral diseaseGenotypeHepatitis C virusGeneGenome

Abstract

fetched live from OpenAlex

Bovine viral diarrhea virus (BVDV), a Pestivirus in the family Flaviviridae, is an economically important pathogen of cattle worldwide. The primary propagators of the virus are immunotolerant persistently infected (PI) cattle, which shed large quantities of virus throughout life. Despite the absence of an acquired immunity against BVDV in these PI cattle there are strong indications of viral variability that are of clinical and epidemiological importance. In this study the variability of E2 and NS5B sequences in multiple body compartments of PI cattle were characterized using clonal sequencing. Phylogenetic analyses revealed that BVDV exists as a quasispecies within PI cattle. Viral variants were clustered by tissue compartment significantly more often than expected by chance alone with the central nervous system appearing to be a particularly important viral reservoir. We also found strong indications for a genetic bottleneck during vertical transmission from PI animals to their offspring. These quasispecies analyses within PI cattle exemplify the role of the PI host in viral propagation and highlight the complex dynamics of BVDV pathogenesis, transmission and evolution.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.101
GPT teacher head0.261
Teacher spread0.161 · 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 designObservational
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

Citations27
Published2015
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicAnimal Disease Management and EpidemiologyFrench-language works237,207