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Atypical multisensory integration in Niemann-Pick type C disease – towards potential biomarkers

Overview of attention for article published in Orphanet Journal of Rare Diseases, September 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)

Mentioned by

twitter
4 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
46 Mendeley
citeulike
1 CiteULike
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Title
Atypical multisensory integration in Niemann-Pick type C disease – towards potential biomarkers
Published in
Orphanet Journal of Rare Diseases, September 2014
DOI 10.1186/s13023-014-0149-x
Pubmed ID
Authors

Gizely N Andrade, Sophie Molholm, John S Butler, Alice B Brandwein, Steven U Walkley, John J Foxe

Abstract

Niemann-Pick type C (NPC) is an autosomal recessive disease in which cholesterol and glycosphingolipids accumulate in lysosomes due to aberrant cell-transport mechanisms. It is characterized by progressive and ultimately terminal neurological disease, but both pre-clinical studies and direct human trials are underway to test the safety and efficacy of cholesterol clearing compounds, with good success already observed in animal models. Key to assessing the effectiveness of interventions in patients, however, is the development of objective neurobiological outcome measures. Multisensory integration mechanisms present as an excellent candidate since they necessarily rely on the fidelity of long-range neural connections between the respective sensory cortices (e.g. the auditory and visual systems).

Twitter Demographics

The data shown below were collected from the profiles of 4 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 45 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 20%
Student > Ph. D. Student 8 17%
Researcher 8 17%
Student > Master 5 11%
Professor 3 7%
Other 10 22%
Unknown 3 7%
Readers by discipline Count As %
Medicine and Dentistry 9 20%
Neuroscience 8 17%
Psychology 7 15%
Nursing and Health Professions 5 11%
Agricultural and Biological Sciences 4 9%
Other 8 17%
Unknown 5 11%

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 05 May 2016.
All research outputs
#12,489,273
of 21,321,525 outputs
Outputs from Orphanet Journal of Rare Diseases
#1,247
of 2,380 outputs
Outputs of similar age
#102,075
of 223,888 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#1
of 1 outputs
Altmetric has tracked 21,321,525 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 2,380 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 46th percentile – i.e., 46% 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 223,888 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them