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Animal Models to Investigate the Pathogenesis of Rheumatic Heart Disease

Overview of attention for article published in Frontiers in Pediatrics, November 2014
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Title
Animal Models to Investigate the Pathogenesis of Rheumatic Heart Disease
Published in
Frontiers in Pediatrics, November 2014
DOI 10.3389/fped.2014.00116
Pubmed ID
Authors

Catherine M. Rush, Brenda L. Govan, Suchandan Sikder, Natasha L. Williams, Natkunam Ketheesan

Abstract

Rheumatic fever (RF) and rheumatic heart disease (RHD) are sequelae of group A streptococcal (GAS) infection. Although an autoimmune process has long been considered to be responsible for the initiation of RF/RHD, it is only in the last few decades that the mechanisms involved in the pathogenesis of the inflammatory condition have been unraveled partly due to experimentation on animal models. RF/RHD is a uniquely human condition and modeling this disease in animals is challenging. Antibody and T cell responses to recombinant GAS M protein (rM) and the subsequent interactions with cardiac tissue have been predominantly investigated using a rat autoimmune valvulitis model. In Lewis rats immunized with rM, the development of hallmark histological features akin to RF/RHD, both in the myocardial and in valvular tissue have been reported, with the generation of heart tissue cross-reactive antibodies and T cells. Recently, a Lewis rat model of Sydenham's chorea and related neuropsychiatric disorders has also been described. Rodent models are very useful for assessing disease mechanisms due to the availability of reagents to precisely determine sequential events following infection with GAS or post-challenge with specific proteins and or carbohydrate preparations from GAS. However, studies of cardiac function are more problematic in such models. In this review, a historical overview of animal models previously used and those that are currently available will be discussed in terms of their usefulness in modeling different aspects of the disease process. Ultimately, cardiologists, microbiologists, immunologists, and physiologists may have to resort to diverse models to investigate different aspects of RF/RHD.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 30%
Student > Bachelor 5 19%
Student > Ph. D. Student 5 19%
Student > Doctoral Student 2 7%
Professor 1 4%
Other 3 11%
Unknown 3 11%
Readers by discipline Count As %
Medicine and Dentistry 10 37%
Immunology and Microbiology 6 22%
Agricultural and Biological Sciences 5 19%
Biochemistry, Genetics and Molecular Biology 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Other 2 7%
Unknown 2 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 06 November 2014.
All research outputs
#7,348,066
of 22,769,322 outputs
Outputs from Frontiers in Pediatrics
#1,324
of 5,927 outputs
Outputs of similar age
#85,046
of 262,191 outputs
Outputs of similar age from Frontiers in Pediatrics
#8
of 33 outputs
Altmetric has tracked 22,769,322 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 5,927 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 77% of its peers.
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 262,191 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 67% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.