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Record W2321356279 · doi:10.1093/ve/vew004

Driving forces behind the evolution of the Aleutian mink disease parvovirus in the context of intensive farming

2016· article· en· W2321356279 on OpenAlexafffundabout
Marta Canuti, Kimberly E. O’Leary, Bruce Hunter, Grant Spearman, Davor Ojkić, Hugh Whitney, Andrew S. Lang

Bibliographic record

VenueVirus Evolution · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsNova Scotia Department of AgricultureUniversity of GuelphGovernment of Newfoundland and LabradorMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Guelph
KeywordsMinkBiologyContext (archaeology)OutbreakPopulationVirologyParvovirusVirusEcologyDemography

Abstract

fetched live from OpenAlex

Aleutian mink disease virus (AMDV) causes plasmacytosis, an immune complex-associated syndrome that affects wild and farmed mink. The virus can also infect other small mammals (e.g., ferrets, skunks, ermines, and raccoons), but the disease in these hosts has been studied less. In 2007, a mink plasmacytosis outbreak began on the Island of Newfoundland, and the virus has been endemic in farms since then. In this study, we evaluated the molecular epidemiology of AMDV in farmed and wild animals of Newfoundland since before the beginning of the outbreak and investigated the epidemic in a global context by studying AMDV worldwide, thereby examining its diffusion and phylogeography. Furthermore, AMDV evolution was examined in the context of intensive farming, where host population dynamics strongly influence viral evolution. Partial NS1 sequences and several complete genomes were obtained from Newfoundland viruses and analyzed along with numerous sequences from other locations worldwide that were either obtained as part of this study or from public databases. We observed very high viral diversity within Newfoundland and within single farms, where high rates of co-infection, recombinant viruses and polymorphisms were observed within single infected individuals. Worldwide, we documented a partial geographic distribution of strains, where viruses from different countries co-exist within clades but form country-specific subclades. Finally, we observed the occurrence of recombination and the predominance of negative selection pressure on AMDV proteins. A surprisingly low number of immunoepitopic sites were under diversifying pressure, possibly because AMDV gains no benefit by escaping the immune response as viral entry into target cells is mediated through interactions with antibodies, which therefore contribute to cell infection. In conclusion, the high prevalence of AMDV in farms facilitates the establishment of co-infections that can favor the occurrence of recombination and enhance viral diversity. Viruses are then exchanged between different farms and countries and can be introduced into the wild, with the rapidly evolving viruses producing many parallel lineages.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.271
Teacher spread0.258 · 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 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

Citations54
Published2016
Admission routes3
Has abstractyes

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