scholarly journals Updating the Quarantine Status of Prunus Infecting Viruses in Australia

Viruses ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 246 ◽  
Author(s):  
Wycliff M. Kinoti ◽  
Narelle Nancarrow ◽  
Alison Dann ◽  
Brendan C. Rodoni ◽  
Fiona E. Constable
Keyword(s):  
Polymerase Chain Reaction ◽  
High Throughput Sequencing ◽  
Mottle Virus ◽  
Rt Pcr ◽  
Chain Reaction ◽  
Virus Family ◽  
First Report ◽  
Hop Stunt Viroid ◽  
Polymerase Chain ◽  
Stem Pitting

One hundred Prunus trees, including almond (P. dulcis), apricot (P. armeniaca), nectarine (P. persica var. nucipersica), peach (P. persica), plum (P. domestica), purple leaf plum (P. cerasifera) and sweet cherry (P. avium), were selected from growing regions Australia-wide and tested for the presence of 34 viruses and three viroids using species-specific reverse transcription-polymerase chain reaction (RT-PCR) or polymerase chain reaction (PCR) tests. In addition, the samples were tested using some virus family or genus-based RT-PCR tests. The following viruses were detected: Apple chlorotic leaf spot virus (ACLSV) (13/100), Apple mosaic virus (ApMV) (1/100), Cherry green ring mottle virus (CGRMV) (4/100), Cherry necrotic rusty mottle virus (CNRMV) (2/100), Cherry virus A (CVA) (14/100), Little cherry virus 2 (LChV2) (3/100), Plum bark necrosis stem pitting associated virus (PBNSPaV) (4/100), Prune dwarf virus (PDV) (3/100), Prunus necrotic ringspot virus (PNRSV) (52/100), Hop stunt viroid (HSVd) (9/100) and Peach latent mosaic viroid (PLMVd) (6/100). The results showed that PNRSV is widespread in Prunus trees in Australia. Metagenomic high-throughput sequencing (HTS) and bioinformatics analysis were used to characterise the genomes of some viruses that were detected by RT-PCR tests and Apricot latent virus (ApLV), Apricot vein clearing associated virus (AVCaV), Asian Prunus Virus 2 (APV2) and Nectarine stem pitting-associated virus (NSPaV) were also detected. This is the first report of ApLV, APV2, CGRMV, CNRNV, LChV1, LChV2, NSPaV and PBNSPaV occurring in Australia. It is also the first report of ASGV infecting Prunus species in Australia, although it is known to infect other plant species including pome fruit and citrus.

scholarly journals First Report of Rupestris stem pitting associated virus in Argentina

Plant Disease ◽  
2002 ◽  
Vol 86 (8) ◽  
pp. 921-921 ◽  
Author(s):  
C. G. Tarnowski ◽  
P. A. Worlock ◽  
S. Ulanovsky ◽  
S. Gómez Talquenca
Keyword(s):  
Polymerase Chain Reaction ◽  
Reverse Transcription ◽  
Polymerase Chain Reaction Method ◽  
Vitis Vinifera L ◽  
Chain Reaction ◽  
First Report ◽  
Cornell University ◽  
Polymerase Chain ◽  
Rupestris Stem Pitting ◽  
Stem Pitting

Rupestris stem pitting associated virus (RSPaV), a component of the rugose wood complex (RWC), is a worldwide graft transmissible disease of grapevines (Vitis vinifera L.). RSPaV has a single-stranded 8,726-nt RNA genome, belongs to the genus Foveavirus, and is often associated with Rupestris stem pitting (RSP) disease (2). In 1995, a grapevine sanitary selection program was implemented in Mendoza to investigate this and other grapevine viral diseases. RSP can be diagnosed when V. rupestris cv. St. George is used as a woody indicator for biological indexing. Chip-bud inoculated St. George plants developed a row of small pits and grooves on the wood cylinder below the graft or around and below the inoculated point (1,2). After three seasons in the field, 15 accessions with RSP wood markings were observed. Mature leaves and bark shavings were extracted, partially purified, and analyzed by a onestep reverse transcription polymerase chain reaction method. The expected 339-bp band was found in only six of the positively indexed samples using the specific 13/14 primer pair (2). Other viruses associated with RWC have been detected in Argentina, but to our knowledge, this is the first report of RSPaV. References: (1) A. C. Goheen. Page 53 in: Compendium of Grape Diseases, R. C. Pearson and A. C. Goheen, eds. American Phytopatological Society, St. Paul, MN, 1988. (2) B. Meng. Rupestris stem pitting: Insights on etiology and development of reverse transcription-polymerase chain reaction and immunoassays for diagnosis. Ph.D. Diss. Cornell University, Ithaca, NY, 1999.

scholarly journals First Report of a Lettuce-Infecting Sequivirus in Chile

Plant Disease ◽  
2005 ◽  
Vol 89 (10) ◽  
pp. 1129-1129 ◽  
Author(s):  
R. Krause-Sakate ◽  
A. S. Jadão ◽  
A. C. Firmino ◽  
M. A. Pavan ◽  
F. M. Zerbini ◽  
...  
Keyword(s):  
Polymerase Chain Reaction ◽  
Mosaic Virus ◽  
Plant Viruses ◽  
Yellow Mosaic Virus ◽  
Mixed Infections ◽  
Replicase Gene ◽  
Rt Pcr ◽  
Chain Reaction ◽  
First Report ◽  
Polymerase Chain

Sequiviruses are isometric aphidborne plant viruses. Dandelion yellow mosaic virus (DaYMV), genus Sequivirus, was isolated from dandelion and lettuce in Europe. Lettuce mottle virus (LeMoV), a putative sequivirus, is often found in mixed infections with Lettuce mosaic virus (LMV) in Brazil (3). DaYMV, LeMoV and LMV cause similar mosaics in field-grown lettuce. Differences in biology and sequence suggest that DaYMV and LeMoV are distinct species (2). Forty-two and 101 lettuce samples with mosaic symptoms collected from two locations near Santiago during a survey of lettuce viruses in Chile in 2002 and 2003, respectively, were analyzed for the presence of LeMoV using reverse transcription polymerase chain reaction (RT-PCR). Total RNA was extracted (1) and used for RT-PCR with the specific LeMoV primers pairs Lmo3 (5′ ACATGAGCACTAGTGAGG 3′) and Lmo4 (5′ AGATAGAGCCGTCT GGCG 3′) (2). One of the 42 and three of the 101 samples produced the expected 300-bp fragment. Isometric particles of 30 nm diameter, typical of a sequivirus, were visualized by transmission electron microscopy. These samples were tested using RT-PCR for the presence of LMV and Cucumber mosaic virus (CMV), but no mixed infections were observed. One isolate, Ch36, was reamplified with the degenerate primer pairs DALE 1 (5′ GARTTCAACATGCACGCCAG 3′) and DALE 2 (5′ TTTTTCTCCCCATYCGTCAT 3′) which amplify part of the putative replicase gene (2) and produced a 563-bp fragment that was cloned on pGEM-T Easy (Promega, Madison, WI) and sequenced. The Ch36 product (EMBL Accession No. AM039965) showed 97% amino acid identity with LeMoV from Brazil, 79% with DaYMV, 72% with the sequivirus Parsnip yellow fleck virus, and 34% with the waikavirus Maize chlorotic dwarf virus. To our knowledge, this is the first report of a sequivirus in field lettuce in Chile, and although the virus was found at low incidence, this report extends the range of LeMoV to the western side of the Cordillera de Los Andes. The impact of LeMoV needs to be further analyzed in Chile, Brazil, and possibly other South American countries. References: (1) Y. D. Bertheau et al. DNA amplification by polymerase chain reaction (PCR) 1998. In: Methods for the Detection and Quantification of Erwinia carotovora subsp. atroseptica on potatoes. M. C. N. Perombelon and J. M. van der Wolff, eds. Scott. Crop Res. Inst. Occasional Publ., Dundee, 1998. (2) A. S. Jadão. Caracterização parcial e desenvolvimento de oligonucleotídeos específicos para detecção de sequivirus infectando alface. Ph.D. thesis. FCA-UNESP-Botucatu, Brazil, 2004. (3) O. Stangarlin et al. Plant Dis. 84:490, 2000.

scholarly journals The occurrence of Apple stem pitting virus and Apple stem grooving virus within field-grown apple cultivars evaluated by RT-PCR

2011 ◽  
Vol 39 (No. 3) ◽  
pp. 88-92 ◽  
Author(s):  
J.K. Kundu
Keyword(s):  
Polymerase Chain Reaction ◽  
Mixed Infection ◽  
Rt Pcr ◽  
Chain Reaction ◽  
Apple Stem Grooving Virus ◽  
Apple Stem ◽  
Apple Cultivars ◽  
Polymerase Chain ◽  
Apple Stem Pitting Virus ◽  
Stem Pitting

The reverse transcription polymerase chain reaction (RT-PCR) was successfully used to determine the occurrence of Apple stem pitting virus (ASPV) and Apple stem grooving virus (ASGV) in field-grown apple cultivars. Both viruses were detected frequently in all 16 tested apple cultivars. As many as 27.86% ASPV-infected and 44% ASGV-infected trees were recorded among a total of 420 tested trees from 15 different orchards. Mixed infection with ASGV and ASPV was recorded in 16.7% of the trees.  

1504: Molecular Diagnosis and Staging of Prostate Cancer Using Clusterin in Real Time Reverse Transcription Polymerase Chain Reaction (RT-PCR)

2006 ◽  
Vol 175 (4S) ◽  
pp. 485-486
Author(s):  
Sabarinath B. Nair ◽  
Christodoulos Pipinikas ◽  
Roger Kirby ◽  
Nick Carter ◽  
Christiane Fenske
Keyword(s):  
Prostate Cancer ◽  
Polymerase Chain Reaction ◽  
Real Time ◽  
Molecular Diagnosis ◽  
Reverse Transcription ◽  
Rt Pcr ◽  
Chain Reaction ◽  
Polymerase Chain

Polymerase chain reaction amplification and typing of rotavirus in environmental samples

1995 ◽  
Vol 31 (5-6) ◽  
pp. 371-374 ◽  
Author(s):  
R. Gajardo ◽  
R. M. Pintó ◽  
A. Bosch
Keyword(s):  
Polymerase Chain Reaction ◽  
Environmental Samples ◽  
Polymerase Chain Reaction Amplification ◽  
Rt Pcr ◽  
Chain Reaction ◽  
Pcr Assay ◽  
Group A ◽  
Reaction Amplification ◽  
Stool Specimens ◽  
Polymerase Chain

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.

scholarly journals Machine Learning Prediction of SARS-CoV-2 Polymerase Chain Reaction Results with Routine Blood Tests

2020 ◽  
Author(s):  
Thomas Tschoellitsch ◽  
Martin Dünser ◽  
Carl Böck ◽  
Karin Schwarzbauer ◽  
Jens Meier
Keyword(s):  
Machine Learning ◽  
Polymerase Chain Reaction ◽  
Characteristic Curve ◽  
Cohort Analysis ◽  
Rt Pcr ◽  
Chain Reaction ◽  
Blood Tests ◽  
Routine Blood ◽  
Machine Learning Model ◽  
Polymerase Chain

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.

scholarly journals A meta-analysis of accuracy and sensitivity of chest CT and RT-PCR in COVID-19 diagnosis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fatemeh Khatami ◽  
Mohammad Saatchi ◽  
Seyed Saeed Tamehri Zadeh ◽  
Zahra Sadat Aghamir ◽  
Alireza Namazi Shabestari ◽  
...  
Keyword(s):  
Polymerase Chain Reaction ◽  
Reverse Transcriptase ◽  
Ct Scan ◽  
Predictive Value ◽  
Meta Analysis ◽  
Chest Ct ◽  
Rt Pcr ◽  
Chain Reaction ◽  
Polymerase Chain ◽  
Chest Ct Scan

AbstractNowadays there is an ongoing acute respiratory outbreak caused by the novel highly contagious coronavirus (COVID-19). The diagnostic protocol is based on quantitative reverse-transcription polymerase chain reaction (RT-PCR) and chests CT scan, with uncertain accuracy. This meta-analysis study determines the diagnostic value of an initial chest CT scan in patients with COVID-19 infection in comparison with RT-PCR. Three main databases; PubMed (MEDLINE), Scopus, and EMBASE were systematically searched for all published literature from January 1st, 2019, to the 21st May 2020 with the keywords "COVID19 virus", "2019 novel coronavirus", "Wuhan coronavirus", "2019-nCoV", "X-Ray Computed Tomography", "Polymerase Chain Reaction", "Reverse Transcriptase PCR", and "PCR Reverse Transcriptase". All relevant case-series, cross-sectional, and cohort studies were selected. Data extraction and analysis were performed using STATA v.14.0SE (College Station, TX, USA) and RevMan 5. Among 1022 articles, 60 studies were eligible for totalizing 5744 patients. The overall sensitivity, specificity, positive predictive value, and negative predictive value of chest CT scan compared to RT-PCR were 87% (95% CI 85–90%), 46% (95% CI 29–63%), 69% (95% CI 56–72%), and 89% (95% CI 82–96%), respectively. It is important to rely on the repeated RT-PCR three times to give 99% accuracy, especially in negative samples. Regarding the overall diagnostic sensitivity of 87% for chest CT, the RT-PCR testing is essential and should be repeated to escape misdiagnosis.

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