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Atypical Porcine Pestivirus as a Novel Type of Pestivirus in Pigs in China

Overview of attention for article published in Frontiers in Microbiology, May 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

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13 news outlets
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1 X user

Citations

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57 Dimensions

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43 Mendeley
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Title
Atypical Porcine Pestivirus as a Novel Type of Pestivirus in Pigs in China
Published in
Frontiers in Microbiology, May 2017
DOI 10.3389/fmicb.2017.00862
Pubmed ID
Authors

Jin Yuan, Zhiyong Han, Jun Li, Yunzhen Huang, Jiongfeng Yang, Hongxing Ding, Jingyuan Zhang, Mengjiao Zhu, Yangyi Zhang, Jiedan Liao, Mingqiu Zhao, Jinding Chen

Abstract

Pestiviruses are highly variable RNA viruses. A growing number of novel pestiviruses has been discovered in domestic and wild species in the last two decades. Recently, a novel atypical porcine pestivirus (APPV) linked with the development of congenital tremor (CT) in neonatal pigs was described in Europe and the Americas. Here, the first Asian APPV complete polyprotein coding sequence was assembled from serum samples from newborn piglets affected with CT in Southern China, and termed APPV_GD. 14 organ samples from affected piglets were analyzed by quantitative RT-PCR (qRT-PCR) to investigate the tissue tropism of APPV, and 135 serum samples from pigs from 10 farms were used for identifying APPV in adult pigs. The highest genome loads were found in submaxillary lymph nodes, and PCR-based detection showed that APPV genomes were present in seven samples from five farms. A phylogenetic tree was constructed based on the full-length genomes of the pestiviruses, and APPV_GD appeared on a new branch with another newly discovered APPV. Nucleotide identity analysis demonstrated that APPV_GD shared the highest nucleotide sequence identity with a German APPV. Bayesian inference was performed using 25 partial sequences of the APPV NS5B gene (528 bp) isolated from four countries in recent years. According to this analysis, the most recent common ancestor (tMRCA) of the current APPV strains might have emerged in Germany and then diversified and spread to Asia, the Americas, and other countries in Europe. However, the result of bayesian inference could change when more APPV strains are isolated in the future. The present study is the first to report APPV in China and infers the origin and dissemination of the current strains of the virus.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 19%
Student > Bachelor 5 12%
Student > Doctoral Student 5 12%
Researcher 5 12%
Student > Master 4 9%
Other 5 12%
Unknown 11 26%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 12 28%
Agricultural and Biological Sciences 8 19%
Biochemistry, Genetics and Molecular Biology 4 9%
Environmental Science 2 5%
Immunology and Microbiology 1 2%
Other 2 5%
Unknown 14 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 106. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 May 2017.
All research outputs
#344,265
of 23,341,064 outputs
Outputs from Frontiers in Microbiology
#172
of 25,675 outputs
Outputs of similar age
#7,886
of 311,736 outputs
Outputs of similar age from Frontiers in Microbiology
#7
of 520 outputs
Altmetric has tracked 23,341,064 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 25,675 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 311,736 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 520 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.