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Record W3080832262 · doi:10.3390/v12090941

Molecular Characterization of Hemorrhagic Enteritis Virus (HEV) Obtained from Clinical Samples in Western Canada 2017–2018

2020· article· en· W3080832262 on OpenAlexafffundabout
Victor Palomino-Tapia, Darko Mitevski, Tom Inglis, Frank van der Meer, Mohamed Faizal Abdul-Careem

Bibliographic record

VenueViruses · 2020
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of Calgary
FundersMitacsAlberta Agriculture and Forestry
KeywordsFlockVirologyVaccinationBiologyEnteritisVirusViral sheddingVirulenceHepatitis E virusMicrobiologyGeneGenotypeGenetics

Abstract

fetched live from OpenAlex

Hemorrhagic enteritis virus (HEV) is an immunosuppressive adenovirus that causes an acute clinical disease characterized by hemorrhagic gastroenteritis in 4-week-old turkeys and older. Recurrent incidence of secondary infections (e.g., systemic bacterial infections, cellulitis, and elevated mortality), may be associated with the presence of field-type HEV in Canadian turkey farms. We speculate that field-type HEV and vaccine/vaccine-like strains can be differentiated through analysis of the viral genomes, hexon genes, and the specific virulence factors (e.g., ORF1, E3, and fib knob domain). Nine out of sixteen spleens obtained from cases suspected of immunosuppression by HEV were analyzed. The limited data obtained showed that: (1) field-type HEV circulates in many non-vaccinated western Canadian flocks; (2) field-type HEV circulates in vaccinated flocks with increased recurrent bacterial infections; and (3) the existence of novel point mutations in hexon, ORF1, E3, and specially fib knob domains. This is the first publication showing the circulation of wild-type HEV in HEV-vaccinated flocks in Western Canada, and the usefulness of a novel procedure that allows whole genome sequencing of HEV directly from spleens, without passaging in cell culture or passaging in vivo. Further studies focusing more samples are required to confirm our observations and investigate possible vaccination failure.

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 score0.431
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.098
GPT teacher head0.352
Teacher spread0.253 · 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

Citations14
Published2020
Admission routes3
Has abstractyes

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