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Identification of brain-enriched proteins in the cerebrospinal fluid proteome by LC-MS/MS profiling and mining of the Human Protein Atlas

Overview of attention for article published in Clinical Proteomics, May 2016
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Title
Identification of brain-enriched proteins in the cerebrospinal fluid proteome by LC-MS/MS profiling and mining of the Human Protein Atlas
Published in
Clinical Proteomics, May 2016
DOI 10.1186/s12014-016-9111-3
Pubmed ID
Authors

Ilijana Begcevic, Davor Brinc, Andrei P. Drabovich, Ihor Batruch, Eleftherios P. Diamandis

Abstract

Cerebrospinal fluid (CSF) is a proximal fluid which communicates closely with brain tissue, contains numerous brain-derived proteins and thus represents a promising fluid for discovery of biomarkers of central nervous system (CNS) diseases. The main purpose of this study was to generate an extensive CSF proteome and define brain-related proteins identified in CSF, suitable for development of diagnostic assays. Six non-pathological CSF samples from three female and three male individuals were selected for CSF analysis. Samples were first subjected to strong cation exchange chromatography, followed by LC-MS/MS analysis. Secreted and membrane-bound proteins enriched in the brain tissues were retrieved from the Human Protein Atlas. In total, 2615 proteins were identified in the CSF. The number of proteins identified per individual sample ranged from 1109 to 1421, with inter-individual variability between six samples of 21 %. Based on the Human Protein Atlas, 78 brain-specific proteins found in CSF samples were proposed as a signature of brain-enriched proteins in CSF. A combination of Human Protein Atlas database and experimental search of proteins in specific body fluid can be applied as an initial step in search for disease biomarkers specific for a particular tissue. This signature may be of significant interest for development of novel diagnostics of CNS diseases and identification of drug targets.

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

Geographical breakdown

Country Count As %
Poland 1 2%
Canada 1 2%
Unknown 53 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 25%
Researcher 10 18%
Student > Master 9 16%
Unspecified 5 9%
Other 4 7%
Other 13 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 31%
Biochemistry, Genetics and Molecular Biology 11 20%
Unspecified 8 15%
Neuroscience 7 13%
Chemistry 6 11%
Other 6 11%

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 02 June 2016.
All research outputs
#7,203,630
of 12,480,234 outputs
Outputs from Clinical Proteomics
#72
of 156 outputs
Outputs of similar age
#123,612
of 266,372 outputs
Outputs of similar age from Clinical Proteomics
#2
of 3 outputs
Altmetric has tracked 12,480,234 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 156 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.