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Profile of Circulatory Metabolites in a Relapsing-remitting Animal Model of Multiple Sclerosis using Global Metabolomics.

Overview of attention for article published in Journal of clinical cellular immunology, January 2013
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Article details
Title
Profile of Circulatory Metabolites in a Relapsing-remitting Animal Model of Multiple Sclerosis using Global Metabolomics.
Published in
Journal of clinical cellular immunology, January 2013
DOI 10.4172/2155-9899.1000150
Pubmed ID
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Abstract

Multiple sclerosis (MS) is a chronic inflammatory and demyelinating disease of the CNS. Although, MS is well characterized in terms of the role played by immune cells, cytokines and CNS pathology, nothing is known about the metabolic alterations that occur during the disease process in circulation. Recently, metabolic aberrations have been defined in various disease processes either as contributing to the disease, as potential biomarkers, or as therapeutic targets. Thus in an attempt to define the metabolic alterations that may be associated with MS disease progression, we profiled the plasma metabolites at the chronic phase of disease utilizing relapsing remitting-experimental autoimmune encephalomyelitis (RR-EAE) model in SJL mice. At the chronic phase of the disease (day 45), untargeted global metabolomic profiling of plasma collected from EAE diseased SJL and healthy mice was performed, using a combination of high-throughput liquid-and-gas chromatography with mass spectrometry. A total of 282 metabolites were identified, with significant changes observed in 44 metabolites (32 up-regulated and 12 down-regulated), that mapped to lipid, amino acid, nucleotide and xenobiotic metabolism and distinguished EAE from healthy group (p<0.05, false discovery rate (FDR)<0.23). Mapping the differential metabolite signature to their respective biochemical pathways using the Kyoto Encyclopedia of Genes and Genomics (KEGG) database, we found six major pathways that were significantly altered (containing concerted alterations) or impacted (containing alteration in key junctions). These included bile acid biosynthesis, taurine metabolism, tryptophan and histidine metabolism, linoleic acid and D-arginine metabolism pathways. Overall, this study identified a 44 metabolite signature drawn from various metabolic pathways which correlated well with severity of the EAE disease, suggesting that these metabolic changes could be exploited as (1) biomarkers for EAE/MS progression and (2) to design new treatment paradigms where metabolic interventions could be combined with present and experimental therapeutics to achieve better treatment of MS.

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Mendeley demographics

Mendeley demographics

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.
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Geographical breakdown

Geographical breakdown
Country Count As %
Brazil 1 1%
Austria 1 1%
Unknown 67 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 13 19%
Student > Ph. D. Student 12 17%
Student > Bachelor 5 7%
Other 4 6%
Student > Master 4 6%
Other 13 19%
Unknown 18 26%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 12 17%
Medicine and Dentistry 11 16%
Biochemistry, Genetics and Molecular Biology 9 13%
Neuroscience 4 6%
Immunology and Microbiology 3 4%
Other 8 12%
Unknown 22 32%
Attention Score in Context

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 20 September 2018.
All research outputs
#28,677,544
of 34,457,357 outputs
Outputs from Journal of clinical cellular immunology
#141
of 189 outputs
Outputs of similar age
#289,296
of 346,369 outputs
Outputs of similar age from Journal of clinical cellular immunology
#21
of 30 outputs
Altmetric has tracked 34,457,357 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 189 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 8th percentile – i.e., 8% 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 346,369 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.