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Improved detection of BRAF V600E using allele-specific PCR coupled with external and internal controllers

Overview of attention for article published in Scientific Reports, October 2017
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Title
Improved detection of BRAF V600E using allele-specific PCR coupled with external and internal controllers
Published in
Scientific Reports, October 2017
DOI 10.1038/s41598-017-14140-2
Pubmed ID
Authors

Zhao Yang, Na Zhao, Dong Chen, Kun Wei, Ning Su, Jun-Fu Huang, Han-Qing Xu, Guang-Jie Duan, Wei-Ling Fu, Qing Huang

Abstract

Although traditional allele-specific PCR (tAS-PCR) is a common screening method for BRAF V600E mutations, its lower amplification specificity and mutation selectivity have limited its clinical applications. We hypothesize that these limitations are associated with the weaker specificities of allele-specific primers and the thermodynamic driving forces of DNA polymerase. We used three strategies to circumvent these limitations, namely, modifying allele-specific primers, introducing a competitive external allele-specific controller (i.e., cAS-PCR), and introducing a referenced internal positive controller in the cAS-PCR (i.e., rcAS-PCR). The amplification sensitivities and specificities were influenced by the position of the artificially introduced mismatched nucleotide in the allele-specific primers. Moreover, both cAS-PCR and rcAS-PCR could detect single-copy BRAF V600E alleles with higher mutation selectivity (0.1%) than tAS-PCR. In addition, cAS-PCR eliminated false-negative results caused by various PCR inhibitors that might be present in the DNA solutions. The rcAS-PCR could also be employed to avoid the false-negative results caused by low-abundance input templates in cAS-PCR. In conclusion, rcAS-PCR provides a rapid, simple, and low-cost method for detecting low levels of the mutated BRAF V600E gene.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 20%
Researcher 4 13%
Professor 2 7%
Student > Master 2 7%
Other 1 3%
Other 4 13%
Unknown 11 37%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 23%
Medicine and Dentistry 5 17%
Agricultural and Biological Sciences 4 13%
Nursing and Health Professions 1 3%
Physics and Astronomy 1 3%
Other 1 3%
Unknown 11 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 October 2017.
All research outputs
#20,450,513
of 23,006,268 outputs
Outputs from Scientific Reports
#106,227
of 124,252 outputs
Outputs of similar age
#285,687
of 327,882 outputs
Outputs of similar age from Scientific Reports
#3,824
of 4,698 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 124,252 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 4,698 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.