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Endogenous gene selection for relative quantification PCR and IL6 transcript levels in the PBMC’s of severe and non-severe dengue cases

Overview of attention for article published in BMC Research Notes, August 2018
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Title
Endogenous gene selection for relative quantification PCR and IL6 transcript levels in the PBMC’s of severe and non-severe dengue cases
Published in
BMC Research Notes, August 2018
DOI 10.1186/s13104-018-3620-2
Pubmed ID
Authors

Vigneshwari Easwar Kumar, Cleetus Cherupanakkal, Minna Catherine, Tamilarasu Kadhiravan, Narayanan Parameswaran, Soundravally Rajendiran, Agieshkumar Balakrishna Pillai

Abstract

Dengue viral infection ranges from dengue fever to dengue haemorrhagic fever and lethal dengue shock syndrome. Currently no means are available to monitor the progression of disease. Real time PCR based gene expression analyses are used to find potential molecular markers for effective prediction of dengue clinical outcome. The accuracy of qPCR analysis is strongly dependent on transcript normalization using stably expressed endogenous genes, which if selected imprecisely can lead to misinterpreted results. We aimed to determine the best fit for endogenous gene among six genes namely COX, ACTB, GAPDH, HMBS, HPRT and B2M for dengue viral infection cases. Gene stability was inferred from qPCR data by normalizing with two algorithms geNorm and Normfinder and the rankings generated were validated by gene expression analysis against target gene IL-6. Both the algorithms showed ACTB, HPRT, GAPDH as most stable genes. Normalizing with the stable genes revealed a significant fold change (p < .05) in IL-6 levels of .32, .52, .69, and .62 in non-dengue febrile illness, non severe, severe and All Dengue groups respectively compared to healthy controls. based on our study, we suggest ACTB with HPRT/GAPDH combination for normalization in qPCR for precise quantification of transcripts in dengue infected studies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 24%
Student > Ph. D. Student 4 11%
Student > Bachelor 3 8%
Researcher 3 8%
Student > Doctoral Student 2 5%
Other 4 11%
Unknown 13 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 18%
Medicine and Dentistry 7 18%
Agricultural and Biological Sciences 4 11%
Immunology and Microbiology 4 11%
Veterinary Science and Veterinary Medicine 1 3%
Other 1 3%
Unknown 14 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 04 August 2018.
All research outputs
#20,529,173
of 23,098,660 outputs
Outputs from BMC Research Notes
#3,583
of 4,287 outputs
Outputs of similar age
#288,972
of 331,122 outputs
Outputs of similar age from BMC Research Notes
#118
of 145 outputs
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