کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5672993 | 1593428 | 2017 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Development of a duplex semi-nested PCR assay for detection of classical goose parvovirus and novel goose parvovirus-related virus in sick or dead ducks with short beak and dwarfism syndrome
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
ایمنی شناسی و میکروب شناسی
ویروس شناسی
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چکیده انگلیسی
Duck short beak and dwarfism syndrome (SBDS) is an emerging infectious disease caused by a novel goose parvovirus-related virus (NGPV) in China. Until now, it remains uncertain whether the Cherry Valley ducks and mule ducks with SBDS are co-infected with classical goose parvovirus (GPV) and NGPV. In this study, a duplex semi-nested PCR assay with high specificity and sensitivity was developed for detection of the two viruses. Using the duplex PCR assay, NGPV was tested positive in all the 15 duck flocks with SBDS, whereas classical GPV was not detected in all the 133 sick and dead ducks collected from East China. A total of 87 (91.58%) Cherry Valley ducks aged from 5 to 18Â days and 35 (92.11%) mule ducks aged from 17 to 25Â days were detected positive for NGPV. In the NGPV-positive ducks, the virus detection rates were 81.97% to 8.20% in heart, liver, spleen, lung, kidney, pancreas, bile, thymus, bursa of Fabricius, and brain. The results indicated that NGPV was prevalent in the duck flocks of East China, whereas classical GPV was not detected in Cherry Valley ducks and mule ducks with SBDS. NGPV has extensive tissue tropism in Cherry Valley duck and mule duck, which could invade both the central and peripheral immune organs and break through the blood-brain barrier of ducks.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Virological Methods - Volume 249, November 2017, Pages 165-169
Journal: Journal of Virological Methods - Volume 249, November 2017, Pages 165-169
نویسندگان
Pengfei Li, Ruihua Zhang, Junhao Chen, Dapeng Sun, Jingjing Lan, Shaoli Lin, Shasha Song, Zhijing Xie, Shijin Jiang,