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Characterizing Glioblastoma Heterogeneity via Single-Cell Receptor Quantification

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, July 2018
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

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8 X users

Citations

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28 Dimensions

Readers on

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67 Mendeley
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Title
Characterizing Glioblastoma Heterogeneity via Single-Cell Receptor Quantification
Published in
Frontiers in Bioengineering and Biotechnology, July 2018
DOI 10.3389/fbioe.2018.00092
Pubmed ID
Authors

Si Chen, Thien Le, Brendan A. C. Harley, P. I. Imoukhuede

Abstract

Dysregulation of tyrosine kinase receptor (RTK) signaling pathways play important roles in glioblastoma (GBM). However, therapies targeting these signaling pathways have not been successful, partially because of drug resistance. Increasing evidence suggests that tumor heterogeneity, more specifically, GBM-associated stem and endothelial cell heterogeneity, may contribute to drug resistance. In this perspective article, we introduce a high-throughput, quantitative approach to profile plasma membrane RTKs on single cells. First, we review the roles of RTKs in cancer. Then, we discuss the sources of cell heterogeneity in GBM, providing context to the key cells directing resistance to drugs. Finally, we present our provisionally patented qFlow cytometry approach, and report results of a "proof of concept" patient-derived xenograft GBM study.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 34%
Researcher 10 15%
Student > Master 8 12%
Student > Bachelor 5 7%
Student > Doctoral Student 4 6%
Other 5 7%
Unknown 12 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 21%
Engineering 9 13%
Medicine and Dentistry 7 10%
Agricultural and Biological Sciences 7 10%
Chemistry 5 7%
Other 10 15%
Unknown 15 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 14 February 2022.
All research outputs
#6,308,601
of 23,122,481 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#924
of 6,807 outputs
Outputs of similar age
#108,607
of 326,825 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#20
of 48 outputs
Altmetric has tracked 23,122,481 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 6,807 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 86% 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 326,825 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.