ArticleThe plant pathology journal2024
RT-RPA Assay Combined with a Lateral Flow Strip to Detect Soybean Mosaic Virus.
Article in The plant pathology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed.
- Calcium signaling in soybean-virus interactions: emerging roles of calcium sensors in antiviral and environmental stress responses.Frontiers in plant science · 2026Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Soybean (Glycine max L.) is one of the most widely planted and used legumes in the world, being used for food, animal feed products, and industrial production. The soybean mosaic virus (SMV) is the most prevalent virus infecting soybean plants. This study developed a diagnostic method for the rapid and sensitive detection of SMV using a reverse transcription-recombinase polymerase amplification (RT-RPA) technique combined with a lateral flow strip (LFS). The RT-RPA and RT-RPA-LFS conditions to detect the SMV were optimized using the selected primer set that amplified part of the VPg protein gene. The optimized reaction temperature for the RT-RPA primer and RT-RPA-LFS primer used in this study was 38℃ for both, and the minimum reaction time was 10 min and 5 min, respectively. The RT-RPA-LFS was as sensitive as RT-PCR to detect SMV with 10 pg/μl of total RNA. The reliability of the developed RT-RPA-LFS assay was evaluated using leaves collected from soybean fields. The RT-RPA-LFS diagnostic method developed in this study will be useful as a diagnostic method that can quickly and precisely detect SMV in the epidemiological investigation of SMV, in the selection process of SMV-resistant varieties, on local farms with limited resources.
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Registered trials
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