Molecular Detection of Tobacco rattle virus in Bleeding Heart [Dicentra spectabilis (L.) Lem.] Growing in Alaska

2013 ◽  
Vol 14 (1) ◽  
pp. 57
Author(s):  
Nancy L. Robertson

Tobacco rattle virus (TRV) was detected in bleeding heart from South Central Alaskan home gardens in 2010-11. TRV M-type and NM-type isolates were confirmed from these symptomatic bleeding heart plants by reverse transcription (RT)-PCR polymerase chain reaction, protein, serological, and virus transmission assays. RNA1 was sequenced from one of the bleeding heart M-type isolates, and the nucleotide identity ranged from 91% to 94% when compared with six TRV isolates from potato, spinach, and alstroemeria. This is the first detection of TRV from D. spectabilis in Alaska. It is also the first time that M- and NM-type isolates have been distinguished from bleeding heart plants. The significance of these findings is that even though TRV infected plants containing NM-type isolates probably will not be spread to other plants by its specific nematode vector; vegetative propagated roots from TRV infected plants of either type of isolates will continue to be a source of diseased plants to home gardeners. Accepted for publication 18 December 2012. Published 27 February 2013.

2016 ◽  
Vol 31 (1) ◽  
pp. 29-31
Author(s):  
Marieke Brauer ◽  
Marianne Wolfaardt ◽  
Lynne M. Webber ◽  
Maureen B. Taylor

The study aimed to determine the presence of mumps virus (MuV) in cerebrospinal fluid (CSF) specimens and to genetically characterise detected MuV strains. A real-time reverse transcription-polymerase chain reaction (RT-PCR) was used to detect the MuV F gene, and characterisation was performed by sequencing of the SH gene. Mumps virus was detected in 1.2% (3/260) of specimens. Phylogenetic analysis of one MuV strain revealed that it clustered with the Jeryl-Lynn and RIT4385 vaccine strains. As far as the authors could ascertain this is the first study to provide viral proof that these vaccine-like strains may be associated with aseptic meningitis.


2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Grace Trovancia ◽  
Angle Sorisi ◽  
Josef S.B. Tuda

Abstract: Dengue hemorrhagic fever is an acute disease with clinical manifestations of hemorrhage caused by dengue virus infection. Manado is endemic dengue. Dengue virus has the ability to maintain its existence in nature through horizontal and vertical transmission. There are several ways to detect the dengue virus by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and immunohistochemistry Streptavidin Biotin Peroxidase Complex (ISBPC). This research aims to determine the wild Aedes aegypti population in Manado and to detect dengue virus in wild mosquito Aedes aegypti by ISBPC methods. This was a descriptive survey study with a cross sectional design to describe the transmission of dengue virus in wild mosquito Aedes aegypti in the city of Manado. The results showed that there were 5 wild Aedes aegypti mosquitoes positive for dengue virus, and 36 wild Aedes aegypti mosquitoes negative containing dengue virus. Conclusion: Of the 41 samples immunohistochemistry tested, 5 samples showed dengue virus transmission in wild mosquito Aedes aegypti in Manado which is a positive possibility of horizontal transmission.Keywords: detection of dengue virus, transmission, wild Aedes aegypti, Manado. Abstrak: Demam berdarah dengue adalah suatu penyakit akut dengan manifestasi klinis perdarahan yang disebabkan oleh infeksi virus dengue. Manado merupakan daerah endemis demam berdarah. Virus dengue memiliki kemampuan untuk mempertahankan keberadaannya di alam melalui transmisi horizontal dan vertikal. Ada beberapa cara untuk mendeteksi virus dengue yaitu Reverse Transcription-Polymerase Chain Reaction (RT-PCR) dan imunohistokimia Streptavidin Biotin Peroxidase Complex (SBPC). Penelitian ini bertujuan untuk mengetahui populasi nyamuk wild Aedes aegypti di Kota Manado dan mendeteksi virus dengue pada nyamuk wild Aedes aegypti dewasa menggunakan metode imunohistokimia streptavidin biotin peroxidase complex (ISBPC). Jenis penelitian ialah survei deskriptif dengan desain potong lintang untuk mengetahui gambaran transmisi virus dengue pada nyamuk wild Aedes aegypti betina di Kota Manado. Hasil pene;itian mendapatkan 5 nyamuk wild Aedes aegypti positif mengandung virus dengue, dan 36 nyamuk wild Aedes aegypti negatif mengandung virus dengue. Simpulan: Berdasarkan hasil penelitian dapat disimpulkan bahwa dari 41 sampel yang telah diuji imunohistokimia, 5 sampel gambaran transmisi virus dengue pada nyamuk wild Aedes aegypti betina di Kota Manado yang kemungkinan transmisi horizontal adalah positif. Kata kunci: deteksi virus dengue, transmisi, wild Aedes aegypti, Manado.


2006 ◽  
Vol 175 (4S) ◽  
pp. 485-486
Author(s):  
Sabarinath B. Nair ◽  
Christodoulos Pipinikas ◽  
Roger Kirby ◽  
Nick Carter ◽  
Christiane Fenske

1995 ◽  
Vol 31 (5-6) ◽  
pp. 371-374 ◽  
Author(s):  
R. Gajardo ◽  
R. M. Pintó ◽  
A. Bosch

A reverse transcription polymerase chain reaction (RT-PCR) assay is described that has been developed for the detection and serotyping of group A rotavirus in stool specimens and concentrated and non-concentrated sewage specimens.


2020 ◽  
Author(s):  
Thomas Tschoellitsch ◽  
Martin Dünser ◽  
Carl Böck ◽  
Karin Schwarzbauer ◽  
Jens Meier

Abstract Objective The diagnosis of COVID-19 is based on the detection of SARS-CoV-2 in respiratory secretions, blood, or stool. Currently, reverse transcription polymerase chain reaction (RT-PCR) is the most commonly used method to test for SARS-CoV-2. Methods In this retrospective cohort analysis, we evaluated whether machine learning could exclude SARS-CoV-2 infection using routinely available laboratory values. A Random Forests algorithm with 1353 unique features was trained to predict the RT-PCR results. Results Out of 12,848 patients undergoing SARS-CoV-2 testing, routine blood tests were simultaneously performed in 1528 patients. The machine learning model could predict SARS-CoV-2 test results with an accuracy of 86% and an area under the receiver operating characteristic curve of 0.90. Conclusion Machine learning methods can reliably predict a negative SARS-CoV-2 RT-PCR test result using standard blood tests.


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