Evidence map›Paper›PMID 35831457›Full record

ArticleScientific reports2022

Rapid, in-field deployable, avian influenza virus haemagglutinin characterisation tool using MinION technology.

Ellen M de Vries, Noel O I Cogan, Aneta J Gubala, Peter T Mee, Kim J O'Riley, Brendan C Rodoni, Stacey E Lynch

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
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  7. Review
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  10. Nanopore sequencing in veterinary medicine: from concepts to clinical applications.Frontiers in cellular and infection microbiology · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Ellen M de VriesAgriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia. ellen.devries@agriculture.vic.gov.au.
Noel O I CoganAgriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Aneta J GubalaLand Division, Defence Science & Technology Group, Fishermans Bend, VIC, 3207, Australia.
Peter T MeeAgriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Kim J O'RileyAgriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Brendan C RodoniAgriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
Stacey E LynchAgriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
AgriBio · AUAgriculture Victoria · AUDefence Science and Technology Group · AULa Trobe University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Outbreaks of avian influenza virus (AIV) from wild waterfowl into the poultry industry is of upmost significance and is an ongoing and constant threat to the industry. Accurate surveillance of AIV in wild waterfowl is critical in understanding viral diversity in the natural reservoir. Current surveillance methods for AIV involve collection of samples and transportation to a laboratory for molecular diagnostics. Processing of samples using this approach takes more than three days and may limit testing locations to those with practical access to laboratories. In potential outbreak situations, response times are critical, and delays have implications in terms of the spread of the virus that leads to increased economic cost. This study used nanopore sequencing technology for in-field sequencing and subtype characterisation of AIV strains collected from wild bird faeces and poultry. A custom in-field virus screening and sequencing protocol, including a targeted offline bioinformatic pipeline, was developed to accurately subtype AIV. Due to the lack of optimal diagnostic MinION packages for Australian AIV strains the bioinformatic pipeline was specifically targeted to confidently subtype local strains. The method presented eliminates the transportation of samples, dependence on internet access and delivers critical diagnostic information in a timely manner.

Indexed as

Influenza A virusInfluenza in BirdsTool Use BehaviorAnimalsAustraliaHemagglutininsPoultryTechnologyHemagglutinins

Identifiers

PMID35831457
PMCPMC9279447
OpenAlexW4285085014

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.