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Record W4390987220 · doi:10.1002/jmv.29401

First detection and characterization of hepatitis E virus (<i>Rocahepevirus ratti</i>) from urban Norway rats (<i>Rattus norvegicus</i>) in the Republic of Korea

2024· article· en· W4390987220 on OpenAlexaff
Kyungmin Park, Jongwoo Kim, Juyoung Noh, Kijin Kim, Eun-Young Yang, Seong‐Gyu Kim, Hee‐Kyung Cho, Kwan Soo Byun, Ji Hoon Kim, Young‐Sun Lee, Jung Ok Shim, Minsoo Shin, Won‐Keun Kim, Jin‐Won Song

Bibliographic record

VenueJournal of Medical Virology · 2024
Typearticle
Languageen
FieldMedicine
TopicHepatitis Viruses Studies and Epidemiology
Canadian institutionsSimon Fraser University
FundersIllinois Bar Foundation
KeywordsHepatitis E virusZoonosisVirologyBiologyGenotypeHepatitis EMolecular epidemiologyTransmission (telecommunications)Phylogenetic treeGeneticsGene

Abstract

fetched live from OpenAlex

Hepatitis E virus (HEV), an emerging zoonotic pathogen, poses a significant public health concern worldwide. Recently, rat HEV (Rocahepevirus ratti genotype C1; HEV-C1) has been reported to cause zoonotic infections and hepatitis in humans. Human infections with HEV-C1 are considered to be underestimated worldwide due to limited knowledge of transmission routes, genome epidemiology, and the risk assessment of zoonosis associated with these viruses. A total of 186 wild Norway rats (Rattus norvegicus) were collected from the Republic of Korea (ROK) between 2011 and 2021. The prevalence of HEV-C1 RNA was 8 of 180 (4.4%) by reverse-transcription polymerase chain reaction. We first reported three nearly whole-genome sequences of HEV-C1 newly acquired from urban rats in the ROK. Phylogenetic analysis demonstrated that Korea-indigenous HEV-C1 formed an independent genetic group with those derived from R. norvegicus rats in other countries, indicating geographical and genetic diversity. Our findings provide critical insights into the molecular prevalence, genome epidemiology, and zoonotic potential of Rocahepevirus. This report raises awareness of the presence of Rocahepevirus-related hepatitis E among physicians in the ROK.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.279
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 integrity0.0000.001
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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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