↓ Skip to main content

Idiopathic inflammatory myopathies: pathogenic mechanisms of muscle weakness

Overview of attention for article published in Skeletal Muscle, June 2013
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)

Mentioned by

twitter
2 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
55 Dimensions

Readers on

mendeley
129 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Idiopathic inflammatory myopathies: pathogenic mechanisms of muscle weakness
Published in
Skeletal Muscle, June 2013
DOI 10.1186/2044-5040-3-13
Pubmed ID
Authors

Sree Rayavarapu, William Coley, Travis B Kinder, Kanneboyina Nagaraju

Abstract

Idiopathic inflammatory myopathies (IIMs) are a heterogenous group of complex muscle diseases of unknown etiology. These diseases are characterized by progressive muscle weakness and damage, together with involvement of other organ systems. It is generally believed that the autoimmune response (autoreactive lymphocytes and autoantibodies) to skeletal muscle-derived antigens is responsible for the muscle fiber damage and muscle weakness in this group of disorders. Therefore, most of the current therapeutic strategies are directed at either suppressing or modifying immune cell activity. Recent studies have indicated that the underlying mechanisms that mediate muscle damage and dysfunction are multiple and complex. Emerging evidence indicates that not only autoimmune responses but also innate immune and non-immune metabolic pathways contribute to disease pathogenesis. However, the relative contributions of each of these mechanisms to disease pathogenesis are currently unknown. Here we discuss some of these complex pathways, their inter-relationships and their relation to muscle damage in myositis. Understanding the relative contributions of each of these pathways to disease pathogenesis would help us to identify suitable drug targets to alleviate muscle damage and also improve muscle weakness and quality of life for patients suffering from these debilitating muscle diseases.

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

Geographical breakdown

Country Count As %
United States 2 2%
Spain 1 <1%
Canada 1 <1%
Unknown 125 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 17%
Student > Master 19 15%
Researcher 18 14%
Student > Postgraduate 11 9%
Student > Bachelor 9 7%
Other 22 17%
Unknown 28 22%
Readers by discipline Count As %
Medicine and Dentistry 36 28%
Agricultural and Biological Sciences 25 19%
Biochemistry, Genetics and Molecular Biology 13 10%
Neuroscience 6 5%
Immunology and Microbiology 5 4%
Other 15 12%
Unknown 29 22%

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 24 September 2016.
All research outputs
#7,217,694
of 12,504,607 outputs
Outputs from Skeletal Muscle
#196
of 236 outputs
Outputs of similar age
#68,306
of 149,046 outputs
Outputs of similar age from Skeletal Muscle
#1
of 2 outputs
Altmetric has tracked 12,504,607 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 236 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 13th percentile – i.e., 13% 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 149,046 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 51% of its contemporaries.
We're also able to compare this research output to 2 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