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In vitro Models for Seizure-Liability Testing Using Induced Pluripotent Stem Cells

Overview of attention for article published in Frontiers in Neuroscience, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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Title
In vitro Models for Seizure-Liability Testing Using Induced Pluripotent Stem Cells
Published in
Frontiers in Neuroscience, August 2018
DOI 10.3389/fnins.2018.00590
Pubmed ID
Authors

Alastair I. Grainger, Marianne C. King, David A. Nagel, H. Rheinallt Parri, Michael D. Coleman, Eric J. Hill

Abstract

The brain is the most complex organ in the body, controlling our highest functions, as well as regulating myriad processes which incorporate the entire physiological system. The effects of prospective therapeutic entities on the brain and central nervous system (CNS) may potentially cause significant injury, hence, CNS toxicity testing forms part of the "core battery" of safety pharmacology studies. Drug-induced seizure is a major reason for compound attrition during drug development. Currently, the rat ex vivo hippocampal slice assay is the standard option for seizure-liability studies, followed by primary rodent cultures. These models can respond to diverse agents and predict seizure outcome, yet controversy over the relevance, efficacy, and cost of these animal-based methods has led to interest in the development of human-derived models. Existing platforms often utilize rodents, and so lack human receptors and other drug targets, which may produce misleading data, with difficulties in inter-species extrapolation. Current electrophysiological approaches are typically used in a low-throughput capacity and network function may be overlooked. Human-derived induced pluripotent stem cells (iPSCs) are a promising avenue for neurotoxicity testing, increasingly utilized in drug screening and disease modeling. Furthermore, the combination of iPSC-derived models with functional techniques such as multi-electrode array (MEA) analysis can provide information on neuronal network function, with increased sensitivity to neurotoxic effects which disrupt different pathways. The use of an in vitro human iPSC-derived neural model for neurotoxicity studies, combined with high-throughput techniques such as MEA recordings, could be a suitable addition to existing pre-clinical seizure-liability testing strategies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 141 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 141 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 19%
Student > Ph. D. Student 21 15%
Student > Master 17 12%
Student > Bachelor 14 10%
Student > Doctoral Student 11 8%
Other 11 8%
Unknown 40 28%
Readers by discipline Count As %
Neuroscience 37 26%
Biochemistry, Genetics and Molecular Biology 18 13%
Agricultural and Biological Sciences 10 7%
Engineering 9 6%
Pharmacology, Toxicology and Pharmaceutical Science 8 6%
Other 16 11%
Unknown 43 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 27 July 2020.
All research outputs
#2,576,593
of 25,385,509 outputs
Outputs from Frontiers in Neuroscience
#1,587
of 11,542 outputs
Outputs of similar age
#51,392
of 345,542 outputs
Outputs of similar age from Frontiers in Neuroscience
#49
of 244 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. 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 345,542 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 244 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.