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Cells of Matter—In Vitro Models for Myotonic Dystrophy

Overview of attention for article published in Frontiers in Neurology, May 2018
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3 X users

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70 Mendeley
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Title
Cells of Matter—In Vitro Models for Myotonic Dystrophy
Published in
Frontiers in Neurology, May 2018
DOI 10.3389/fneur.2018.00361
Pubmed ID
Authors

Magdalena Matloka, Arnaud F. Klein, Frédérique Rau, Denis Furling

Abstract

Myotonic dystrophy type 1 (DM1 also known as Steinert disease) is a multisystemic disorder mainly characterized by myotonia, progressive muscle weakness and wasting, cognitive impairments, and cardiac defects. This autosomal dominant disease is caused by the expression of nuclear retained RNAs containing pathologic expanded CUG repeats that alter the function of RNA-binding proteins in a tissue-specific manner, leading ultimately to neuromuscular dysfunction and clinical symptoms. Although considerable knowledge has been gathered on myotonic dystrophy since its first description, the development of novel relevant disease models remains of high importance to investigate pathophysiologic mechanisms and to assess new therapeutic approaches. In addition to animal models, in vitro cell cultures provide a unique resource for both fundamental and translational research. This review discusses how cellular models broke ground to decipher molecular basis of DM1 and describes currently available cell models, ranging from exogenous expression of the CTG tracts to variable patients' derived cells.

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

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 19%
Student > Bachelor 10 14%
Researcher 7 10%
Student > Master 7 10%
Student > Postgraduate 3 4%
Other 6 9%
Unknown 24 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 22 31%
Pharmacology, Toxicology and Pharmaceutical Science 5 7%
Agricultural and Biological Sciences 4 6%
Medicine and Dentistry 3 4%
Neuroscience 2 3%
Other 7 10%
Unknown 27 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 29 December 2021.
All research outputs
#14,795,365
of 22,780,165 outputs
Outputs from Frontiers in Neurology
#6,086
of 11,667 outputs
Outputs of similar age
#197,853
of 329,365 outputs
Outputs of similar age from Frontiers in Neurology
#149
of 307 outputs
Altmetric has tracked 22,780,165 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,667 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 43rd percentile – i.e., 43% 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 329,365 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 307 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.