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Untargeted Plasma Metabolomics Identifies Endogenous Metabolite with Drug-like Properties in Chronic Animal Model of Multiple Sclerosis*

Overview of attention for article published in Journal of Biological Chemistry, November 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

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5 X users
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2 patents
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1 Facebook page

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110 Mendeley
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Article details
Title
Untargeted Plasma Metabolomics Identifies Endogenous Metabolite with Drug-like Properties in Chronic Animal Model of Multiple Sclerosis*
Published in
Journal of Biological Chemistry, November 2015
DOI 10.1074/jbc.m115.679068
Pubmed ID
Authors
Abstract

We performed untargeted metabolomics of plasma from B6 mice with experimental autoimmune encephalitis (EAE) at the chronic phase of the disease in search of an altered metabolic pathway(s). Of 324 metabolites measured, 100 metabolites that mapped to various pathways (mainly lipids) linked to mitochondrial function, inflammation and membrane stability were observed to be significantly altered between EAE and healthy control (p < 0.05, false discover rate [< 0.10]. Bioinformatics analysis revealed 6 metabolic pathways being impacted and altered in EAE including alpha linolenic acid and linoleic acid metabolism (PUFA). The metabolites of PUFAs, including omega 3 and omega 6 fatty acids, are commonly decreased in mouse models and in multiple sclerosis patients. Daily oral administration of resolvin D1, a downstream metabolite of omega 3, decreased disease progression by suppressing autoreactive T cells and inducing a M2 phenotype of monocytes/macrophages and resident brain microglial cells. This study provides a proof of principle for the application of a metabolomic approach to identify endogenous metabolite(s) possessing drug-like properties, which is tested for therapy in preclinical mouse models.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 110 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 %
United States 1 <1%
Unknown 109 99%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 17 15%
Student > Ph. D. Student 14 13%
Researcher 14 13%
Student > Doctoral Student 9 8%
Professor 8 7%
Other 14 13%
Unknown 34 31%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 15 14%
Biochemistry, Genetics and Molecular Biology 11 10%
Medicine and Dentistry 10 9%
Immunology and Microbiology 8 7%
Neuroscience 8 7%
Other 14 13%
Unknown 44 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 February 2020.
All research outputs
#4,719,778
of 33,825,399 outputs
Outputs from Journal of Biological Chemistry
#4,131
of 29,479 outputs
Outputs of similar age
#50,834
of 322,552 outputs
Outputs of similar age from Journal of Biological Chemistry
#72
of 503 outputs
Altmetric has tracked 33,825,399 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 29,479 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done well, scoring higher than 85% 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 322,552 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 503 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.