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Lack of human cytomegalovirus expression in single cells from glioblastoma tumors and cell lines

Overview of attention for article published in Journal of NeuroVirology, July 2017
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Title
Lack of human cytomegalovirus expression in single cells from glioblastoma tumors and cell lines
Published in
Journal of NeuroVirology, July 2017
DOI 10.1007/s13365-017-0543-y
Pubmed ID
Authors

Travis S. Johnson, Zachary B. Abrams, Xiaokui Mo, Yan Zhang, Kun Huang

Abstract

The relationship between human cytomegalovirus (HCMV) and glioblastoma (GBM) is an ongoing debate with extensive evidence supporting or refuting its existence through molecular assays, pre-clinical studies, and clinical trials. We focus primarily on the crux of the debate, detection of HCMV in GBM samples using molecular assays. We propose that these differences in detection could be affected by cellular heterogeneity. To take this into account, we align the single-cell RNA sequencing (scRNA-seq) reads from five GBM tumors and two cell lines to HCMV and analyze the alignments for evidence of (i) complete viral transcripts and (ii) low-abundance viral reads. We found that neither tumor nor cell line samples showed conclusive evidence of full HCMV viral transcripts. We also identified low-abundance reads aligned across all tumors, with two tumors having higher alignment rates than the rest of the tumor samples. This work is meant to rigorously test for HCMV RNA expression at a single cell level in GBM samples and examine the possible utility of single cell data in tumor virology.

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The data shown below were collected from the profiles of 2 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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 15%
Student > Master 3 15%
Student > Ph. D. Student 3 15%
Researcher 2 10%
Other 1 5%
Other 3 15%
Unknown 5 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 30%
Medicine and Dentistry 4 20%
Agricultural and Biological Sciences 3 15%
Computer Science 1 5%
Unknown 6 30%
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 12 July 2017.
All research outputs
#18,560,904
of 22,988,380 outputs
Outputs from Journal of NeuroVirology
#661
of 931 outputs
Outputs of similar age
#239,245
of 312,577 outputs
Outputs of similar age from Journal of NeuroVirology
#5
of 13 outputs
Altmetric has tracked 22,988,380 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 931 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 312,577 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.