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Muscle wasting in myotonic dystrophies: a model of premature aging

Overview of attention for article published in Frontiers in Aging Neuroscience, July 2015
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)

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Title
Muscle wasting in myotonic dystrophies: a model of premature aging
Published in
Frontiers in Aging Neuroscience, July 2015
DOI 10.3389/fnagi.2015.00125
Pubmed ID
Authors

Alba Judith Mateos-Aierdi, Maria Goicoechea, Ana Aiastui, Roberto Fernández-Torrón, Mikel Garcia-Puga, Ander Matheu, Adolfo López de Munain

Abstract

Myotonic dystrophy type 1 (DM1 or Steinert's disease) and type 2 (DM2) are multisystem disorders of genetic origin. Progressive muscular weakness, atrophy and myotonia are the most prominent neuromuscular features of these diseases, while other clinical manifestations such as cardiomyopathy, insulin resistance and cataracts are also common. From a clinical perspective, most DM symptoms are interpreted as a result of an accelerated aging (cataracts, muscular weakness and atrophy, cognitive decline, metabolic dysfunction, etc.), including an increased risk of developing tumors. From this point of view, DM1 could be described as a progeroid syndrome since a notable age-dependent dysfunction of all systems occurs. The underlying molecular disorder in DM1 consists of the existence of a pathological (CTG) triplet expansion in the 3' untranslated region (UTR) of the Dystrophia Myotonica Protein Kinase (DMPK) gene, whereas (CCTG)n repeats in the first intron of the Cellular Nucleic acid Binding Protein/Zinc Finger Protein 9 (CNBP/ZNF9) gene cause DM2. The expansions are transcribed into (CUG)n and (CCUG)n-containing RNA, respectively, which form secondary structures and sequester RNA-binding proteins, such as the splicing factor muscleblind-like protein (MBNL), forming nuclear aggregates known as foci. Other splicing factors, such as CUGBP, are also disrupted, leading to a spliceopathy of a large number of downstream genes linked to the clinical features of these diseases. Skeletal muscle regeneration relies on muscle progenitor cells, known as satellite cells, which are activated after muscle damage, and which proliferate and differentiate to muscle cells, thus regenerating the damaged tissue. Satellite cell dysfunction seems to be a common feature of both age-dependent muscle degeneration (sarcopenia) and muscle wasting in DM and other muscle degenerative diseases. This review aims to describe the cellular, molecular and macrostructural processes involved in the muscular degeneration seen in DM patients, highlighting the similarities found with muscle aging.

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The data shown below were collected from the profiles of 6 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 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Denmark 1 <1%
France 1 <1%
Australia 1 <1%
Unknown 176 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 17%
Researcher 30 17%
Student > Master 27 15%
Student > Bachelor 19 11%
Other 10 6%
Other 23 13%
Unknown 40 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 42 23%
Medicine and Dentistry 34 19%
Agricultural and Biological Sciences 24 13%
Neuroscience 8 4%
Nursing and Health Professions 5 3%
Other 24 13%
Unknown 43 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 December 2018.
All research outputs
#13,207,948
of 22,816,807 outputs
Outputs from Frontiers in Aging Neuroscience
#2,847
of 4,773 outputs
Outputs of similar age
#119,642
of 262,224 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#41
of 59 outputs
Altmetric has tracked 22,816,807 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,773 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one is in the 38th percentile – i.e., 38% 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 262,224 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 53% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.