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Definition of a Family of Tissue-Protective Cytokines Using Functional Cluster Analysis: A Proof-of-Concept Study

Overview of attention for article published in Frontiers in immunology, March 2014
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Title
Definition of a Family of Tissue-Protective Cytokines Using Functional Cluster Analysis: A Proof-of-Concept Study
Published in
Frontiers in immunology, March 2014
DOI 10.3389/fimmu.2014.00115
Pubmed ID
Authors

Manuela Mengozzi, Peter Ermilov, Alexander Annenkov, Pietro Ghezzi, Frances Pearl

Abstract

The discovery of the tissue-protective activities of erythropoietin (EPO) has underlined the importance of some cytokines in tissue-protection, repair, and remodeling. As such activities have been reported for other cytokines, we asked whether we could define a class of tissue-protective cytokines. We therefore explored a novel approach based on functional clustering. In this pilot study, we started by analyzing a small number of cytokines (30). We functionally classified the 30 cytokines according to their interactions by using the bioinformatics tool STRING (Search Tool for the Retrieval of Interacting Genes), followed by hierarchical cluster analysis. The results of this functional clustering were different from those obtained by clustering cytokines simply according to their sequence. We previously reported that the protective activity of EPO in a model of cerebral ischemia was paralleled by an upregulation of synaptic plasticity genes, particularly early growth response 2 (EGR2). To assess the predictivity of functional clustering, we tested some of the cytokines clustering close to EPO (interleukin-11, IL-11; kit ligand, KITLG; leukemia inhibitory factor, LIF; thrombopoietin, THPO) in an in vitro model of human neuronal cells for their ability to induce EGR2. Two of these, LIF and IL-11, induced EGR2 expression. Although these data would need to be extended to a larger number of cytokines and the biological validation should be done using more robust in vivo models, rather then just one cell line, this study shows the feasibility of this approach. This type of functional cluster analysis could be extended to other fields of cytokine research and help design biological experiments.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 38%
Unspecified 1 13%
Researcher 1 13%
Student > Master 1 13%
Unknown 2 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 25%
Biochemistry, Genetics and Molecular Biology 1 13%
Unspecified 1 13%
Neuroscience 1 13%
Medicine and Dentistry 1 13%
Other 0 0%
Unknown 2 25%
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 17 March 2014.
All research outputs
#19,962,154
of 25,394,764 outputs
Outputs from Frontiers in immunology
#22,598
of 31,554 outputs
Outputs of similar age
#175,506
of 249,655 outputs
Outputs of similar age from Frontiers in immunology
#62
of 97 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 31,554 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.