↓ Skip to main content

L1 and L2 gene polymorphisms in HPV-58 and HPV-33: implications for vaccine design and diagnosis

Overview of attention for article published in Virology Journal, October 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
4 X users
patent
2 patents
facebook
1 Facebook page

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
46 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
L1 and L2 gene polymorphisms in HPV-58 and HPV-33: implications for vaccine design and diagnosis
Published in
Virology Journal, October 2016
DOI 10.1186/s12985-016-0629-9
Pubmed ID
Authors

Zuyi Chen, Yaling Jing, Qiang Wen, Xianping Ding, Shun Zhang, Tao Wang, Yiwen Zhang, Jianhui Zhang

Abstract

Cervical cancer is associated with infection by certain subtypes of human papillomavirus (HPV). The L1 protein comprising HPV vaccine formulations elicits high-titre neutralizing antibodies and confers protection against specific HPV subtypes. HPV L2 protein is an attractive candidate for cross-protective vaccines. HPV-33 and HPV-58 are very prevalent among Chinese women. To study the gene intratypic variations and polymorphisms of HPV-33 and HPV-58 L1/L2 in Sichuan China, HPV-33 and HPV-58 L1 and L2 genes were sequenced and compared with other genes submitted to GenBank. Phylogenetic trees were constructed by maximum-likelihood and the Kimura 2-parameters methods (MEGA 6). The secondary structure was analyzed by PSIPred software, and HPV-33 and HPV-58 L1 homology models were created by SWISS-MODEL software. The selection pressures acting on the L1/L2 genes were estimated by PAML 4.8. Among 124 HPV-33 L1 sequences 20 single nucleotide mutations were observed included 8/20 non-synonymous and 12/20 synonymous mutations. The 101 HPV-33 L2 sequences included 12 single nucleotide mutations comprising 7/12 non-synonymous and 5/12 synonymous mutations. The 223 HPV-58 L1 sequences included 32 single nucleotide mutations comprising 9/32 non-synonymous and 23/32 synonymous mutations. The 201 HPV-58 L2 sequences comprised 26 single nucleotide mutations including 9/26 non-synonymous and 17/26 synonymous mutations. Selective pressure analysis showed that most of the common non-synonymous mutations showed a positive selection. HPV-33 and HPV-58 L2 were more stable than HPV-33 and HPV-58 L1. HPV-33 and HPV-58 L2 were better candidates as clinical diagnostic targets compared with HPV-33 and HPV-58 L1. Clinical diagnostic probes and second-generation polyvalent vaccines should be designed on the basis of the unique sequence of HPV-33 and 58 L1/L2 variations in Sichuan, to improve the accuracy of clinical detection and the protective efficiency of vaccines.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 20%
Student > Bachelor 6 13%
Student > Ph. D. Student 4 9%
Professor 3 7%
Researcher 3 7%
Other 6 13%
Unknown 15 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 24%
Medicine and Dentistry 5 11%
Agricultural and Biological Sciences 4 9%
Immunology and Microbiology 4 9%
Nursing and Health Professions 3 7%
Other 2 4%
Unknown 17 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 28 January 2021.
All research outputs
#3,420,662
of 23,577,654 outputs
Outputs from Virology Journal
#334
of 3,119 outputs
Outputs of similar age
#59,523
of 322,158 outputs
Outputs of similar age from Virology Journal
#7
of 41 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,119 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one has done well, scoring higher than 88% 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 322,158 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.