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Record W2922702530 · doi:10.1038/s41598-019-40476-y

Pathogenicity of Nipah henipavirus Bangladesh in a swine host

2019· article· en· W2922702530 on OpenAlexaff
Samantha Kasloff, Anders Leung, Bradley Pickering, Gregory A. Smith, Estella Moffat, Brad Collignon, Carissa Embury‐Hyatt, Darwyn Kobasa, Hana M. Weingartl

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsCanadian Science Centre for Human and Animal HealthUniversity of ManitobaPublic Health Agency of CanadaCanadian Food Inspection Agency
Fundersnot available
KeywordsHost (biology)PathogenicityVirologyBiologyMicrobiologyGenetics

Abstract

fetched live from OpenAlex

In 1998 an outbreak of fatal encephalitis among pig farm workers in Malaysia and Singapore led to the discovery of Nipah henipavirus (NiV), a novel paramyxovirus closely related to Hendra henipavirus with case fatality rates of nearly 40%. Following its initial emergence nearly annual outbreaks of NiV have occurred in Bangladesh with a different, NiV Bangladesh, genotype, where the role of pigs in its transmission remains unknown. The present study provides the first report on susceptibility of domestic pigs to NiV Bangladesh following experimental infection, characterizing acute and long-term phases of disease and pathogenesis. All pigs were successfully infected with NiV Bangladesh following oronasal inoculation, with viral shedding confirmed by a novel genotype-specific qRT-PCR in oral, nasal and rectal excretions and dissemination from the upper respiratory tract to the brain, lungs, and associated lymphatic tissues. Unlike previous NiV Malaysia findings in pigs, clinical signs were absent, viremia was undetectable throughout the study, and only low level neutralizing antibody titers were measured by 28/29 days post-NiV-B infection. Results obtained highlight the need for continued and enhanced NiV surveillance in pigs in endemic and at-risk regions, and raise questions regarding applicability of current serological assays to detect animals with previous NiV-B exposure.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.267
Teacher spread0.254 · 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

Citations38
Published2019
Admission routes1
Has abstractyes

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