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First Record of Anguillid Herpesvirus 1 Linked to a Mass Mortality Event in Shortfin Eel (Anguilla bicolor) in Indonesia

2025· article· en· W4409403561 on OpenAlexaboutno aff
Ekky Ilham Romadhona, Handang Widantara, Aslia Aslia, Novi Megawati, Arif Ardiansyah, Annisa Fitri Larassagita, Aditia Farman, Iding Chaidir, Wisnu Sujatmiko, Dedy Yaniharto, Tatag Budiardi, Ratu Siti Aliah, Sutanti Sutanti

Bibliographic record

VenueJurnal Medik Veteriner · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsFisheryBiologyFish <Actinopterygii>Event (particle physics)Geography

Abstract

fetched live from OpenAlex

Anguillid herpesvirus 1 (AngHV-1), a member of the Alloherpesviridae family, is known to cause high mortality in both wild and farmed eels. Notably, no cases of AngHV-1 infection in Indonesia until June 2023, when a significant mortality rate exceeding 75% among cultured glass eels was documented in Bogor, Indonesia. This study investigated the outbreak by collecting 30 diseased fish from multiple cultured tanks to examine clinical symptoms, histopathological changes, and viral presence through PCR targeting the viral DNA polymerase gene. Hemorrhagic lesions in the abdomen and anal regions were the primary clinical symptoms. Histopathological examination revealed hyperplasia, fusion, and epithelial lifting of the gill secondary lamellae. PCR, using 394 bp primer specific for AngHV-1, confirmed 100% infection among the collected samples, indicating rapid viral transmission within the rearing environment. Phylogenetic analysis of partial DNA polymerase amino acid sequences showed that Indonesian AngHV-1 isolate is genetically diverse and shares similarities with strains from China, Taiwan, Canada, and several European countries, suggesting the emergence of a novel strain. This study highlights the urgent need for enhanced biosecurity measures to curb AngHV-1 spread in the Indonesian eel aquaculture sector.

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)0.000
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 score0.274
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.283
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 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

Citations2
Published2025
Admission routes1
Has abstractyes

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