Evidence map›Paper›PMID 38194148›Full record

ArticleArchives of virology2024

Comparison of dye-based and probe-based RT-LAMP in detection of canine astrovirus.

Haixiao Shen, Dequan Yang, Xin Li, Houbin Ju, Feifei Ge, Xianchao Yang, Jian Wang, Luming Xia, Hongjin Zhao, Ping Jiang

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of virology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.2field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

10 authors at 2 institutions in 1 country.

Haixiao Shen *Shanghai Animal Disease Control Center, Shanghai, China.ORCID http://orcid.org/0000-0001-8192-1028
Dequan Yang *Shanghai Animal Disease Control Center, Shanghai, China.
Xin LiShanghai Animal Disease Control Center, Shanghai, China.
Houbin JuShanghai Animal Disease Control Center, Shanghai, China.
Feifei GeShanghai Animal Disease Control Center, Shanghai, China.
Xianchao YangShanghai Animal Disease Control Center, Shanghai, China.
Jian WangShanghai Animal Disease Control Center, Shanghai, China.
Luming XiaShanghai Animal Disease Control Center, Shanghai, China.
Hongjin ZhaoShanghai Animal Disease Control Center, Shanghai, China. zhaohongjin945@163.com.
Ping JiangKey Laboratory of Animal Diseases Diagnostic and Immunology, Ministry of Agriculture, MOE International Joint Collaborative Research Laboratory for Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China. jiangp@njau.edu.cn.
China Animal Disease Control Center · CNNanjing Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A rapid and sensitive assay is essential for reliable surveillance and diagnosis of canine astrovirus (CaAstV). In this study, two real-time reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays with high sensitivity, rapidity, and reliability were developed using fluorescence dye and FRET-based assimilating probes for real-time detection of CaAstV. These assays specifically amplified the ORF2 gene of CaAstV and did not amplify any sequences from canine enterovirus. The limit of detection (LOD) of both the probe-based and dye-based RT-LAMPs was 10

Indexed as

AstroviridaeRNA VirusesAnimalsAntigens, ViralDogsMolecular Diagnostic TechniquesNucleic Acid Amplification TechniquesReal-Time Polymerase Chain ReactionReproducibility of ResultsAntigens, Viral

Identifiers

PMID38194148
OpenAlexW4390706923

What OpenQuestion holds

Textmetadata
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.