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High-Resolution Microfluidic Single-Cell Transcriptional Profiling Reveals Clinically Relevant Subtypes among Human Stem Cell Populations Commonly Utilized in Cell-Based Therapies

Overview of attention for article published in Frontiers in Neurology, March 2016
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Title
High-Resolution Microfluidic Single-Cell Transcriptional Profiling Reveals Clinically Relevant Subtypes among Human Stem Cell Populations Commonly Utilized in Cell-Based Therapies
Published in
Frontiers in Neurology, March 2016
DOI 10.3389/fneur.2016.00041
Pubmed ID
Authors

Robert C. Rennert, Richard Schäfer, Tonya Bliss, Michael Januszyk, Michael Sorkin, Achal S. Achrol, Melanie Rodrigues, Zeshaan N. Maan, Torsten Kluba, Gary K. Steinberg, Geoffrey C. Gurtner

Abstract

Stem cell therapies can promote neural repair and regeneration, yet controversy regarding optimal cell source and mechanism of action has slowed clinical translation, potentially due to undefined cellular heterogeneity. Single-cell resolution is needed to identify clinically relevant subpopulations with the highest therapeutic relevance. We combine single-cell microfluidic analysis with advanced computational modeling to study for the first time two common sources for cell-based therapies, human NSCs and MSCs. This methodology has the potential to logically inform cell source decisions for any clinical application.

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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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 18%
Other 4 14%
Researcher 4 14%
Student > Bachelor 3 11%
Professor 2 7%
Other 5 18%
Unknown 5 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 18%
Engineering 3 11%
Medicine and Dentistry 3 11%
Neuroscience 2 7%
Agricultural and Biological Sciences 1 4%
Other 3 11%
Unknown 11 39%
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 10 April 2016.
All research outputs
#17,793,546
of 22,856,968 outputs
Outputs from Frontiers in Neurology
#7,075
of 11,766 outputs
Outputs of similar age
#205,852
of 300,114 outputs
Outputs of similar age from Frontiers in Neurology
#39
of 56 outputs
Altmetric has tracked 22,856,968 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,766 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 34th percentile – i.e., 34% 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 300,114 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.