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Multiple system atrophy: genetic risks and alpha-synuclein mutations

Overview of attention for article published in F1000 Research, November 2017
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2 tweeters

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69 Mendeley
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Title
Multiple system atrophy: genetic risks and alpha-synuclein mutations
Published in
F1000 Research, November 2017
DOI 10.12688/f1000research.12193.1
Pubmed ID
Authors

Heather T Whittaker, Yichen Qui, Conceição Bettencourt, Henry Houlden

Abstract

Multiple system atrophy (MSA) is one of the few neurodegenerative disorders where we have a significant understanding of the clinical and pathological manifestations but where the aetiology remains almost completely unknown. Research to overcome this hurdle is gaining momentum through international research collaboration and a series of genetic and molecular discoveries in the last few years, which have advanced our knowledge of this rare synucleinopathy. In MSA, the discovery of α-synuclein pathology and glial cytoplasmic inclusions remain the most significant findings. Families with certain types of α-synuclein mutations develop diseases that mimic MSA, and the spectrum of clinical and pathological features in these families suggests a spectrum of severity, from late-onset Parkinson's disease to MSA. Nonetheless, controversies persist, such as the role of common α-synuclein variants in MSA and whether this disorder shares a common mechanism of spreading pathology with other protein misfolding neurodegenerative diseases. Here, we review these issues, specifically focusing on α-synuclein mutations.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 18 26%
Student > Master 11 16%
Researcher 7 10%
Student > Doctoral Student 5 7%
Other 5 7%
Other 10 14%
Unknown 13 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 21 30%
Neuroscience 9 13%
Medicine and Dentistry 6 9%
Agricultural and Biological Sciences 6 9%
Chemistry 3 4%
Other 9 13%
Unknown 15 22%

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 05 March 2018.
All research outputs
#10,079,270
of 12,600,122 outputs
Outputs from F1000 Research
#2,723
of 3,138 outputs
Outputs of similar age
#275,879
of 384,320 outputs
Outputs of similar age from F1000 Research
#144
of 197 outputs
Altmetric has tracked 12,600,122 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,138 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one is in the 6th percentile – i.e., 6% 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 384,320 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 197 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.