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Progerin-Induced Transcriptional Changes in Huntington’s Disease Human Pluripotent Stem Cell-Derived Neurons

Overview of attention for article published in Molecular Neurobiology, December 2019
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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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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1 news outlet
blogs
1 blog
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3 X users

Citations

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16 Dimensions

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54 Mendeley
Title
Progerin-Induced Transcriptional Changes in Huntington’s Disease Human Pluripotent Stem Cell-Derived Neurons
Published in
Molecular Neurobiology, December 2019
DOI 10.1007/s12035-019-01839-8
Pubmed ID
Authors

Dorit Cohen-Carmon, Matan Sorek, Vitaly Lerner, Mundackal S. Divya, Malka Nissim-Rafinia, Yosef Yarom, Eran Meshorer

Abstract

Huntington's disease (HD) is a neurodegenerative late-onset genetic disorder caused by CAG expansions in the coding region of the Huntingtin (HTT) gene, resulting in a poly-glutamine (polyQ) expanded HTT protein. Considerable efforts have been devoted for studying HD and other polyQ diseases using animal models and cell culture systems, but no treatment currently exists. Human embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) offer an elegant solution for modeling human diseases. However, as embryonic or rejuvenated cells, respectively, these pluripotent stem cells (PSCs) do not recapitulate the late-onset feature of the disease. Here, we applied a robust and rapid differentiation protocol to derive electrophysiologically active striatal GABAergic neurons from human wild-type (WT) and HD ESCs and iPSCs. RNA-seq analyses revealed that HD and WT PSC-derived neurons are highly similar in their gene expression patterns. Interestingly, ectopic expression of Progerin in both WT and HD neurons exacerbated the otherwise non-significant changes in gene expression between these cells, revealing IGF1 and genes involved in neurogenesis and nervous system development as consistently altered in the HD cells. This work provides a useful tool for modeling HD in human PSCs and reveals potential molecular targets altered in HD neurons.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 15%
Student > Bachelor 7 13%
Student > Master 5 9%
Student > Doctoral Student 3 6%
Researcher 3 6%
Other 9 17%
Unknown 19 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 28%
Neuroscience 10 19%
Agricultural and Biological Sciences 5 9%
Medicine and Dentistry 3 6%
Nursing and Health Professions 1 2%
Other 1 2%
Unknown 19 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 24 November 2022.
All research outputs
#2,194,134
of 24,871,735 outputs
Outputs from Molecular Neurobiology
#203
of 3,826 outputs
Outputs of similar age
#51,643
of 471,914 outputs
Outputs of similar age from Molecular Neurobiology
#4
of 70 outputs
Altmetric has tracked 24,871,735 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,826 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 94% 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 471,914 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 89% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.