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Design and validation of a disease network of inflammatory processes in the NSG-UC mouse model

Overview of attention for article published in Journal of Translational Medicine, December 2017
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Title
Design and validation of a disease network of inflammatory processes in the NSG-UC mouse model
Published in
Journal of Translational Medicine, December 2017
DOI 10.1186/s12967-017-1368-4
Pubmed ID
Authors

Henrika Jodeleit, Pia Palamides, Florian Beigel, Thomas Mueller, Eckhard Wolf, Matthias Siebeck, Roswitha Gropp

Abstract

Ulcerative colitis (UC) is a highly progressive inflammatory disease that requires the interaction of epithelial, immune, endothelial and muscle cells and fibroblasts. Previous studies suggested two inflammatory conditions in UC-patients: 'acute' and 'remodeling' and that the design of a disease network might improve the understanding of the inflammatory processes. The objective of the study was to design and validate a disease network in the NOD-SCID IL2rγnull (NSG)-UC mouse model to get a better understanding of the inflammatory processes. Leukocytes were isolated from the spleen of NSG-UC mice and subjected to flow cytometric analysis. RT-PCR and RNAseq analysis were performed from distal parts of the colon. Based on these analyses and the effects of interleukins, chemokines and growth factors described in the literature, a disease network was designed. To validate the disease network the effect of infliximab and pitrakinra was tested in the NSG-UC model. A clinical- and histological score, frequencies of human leukocytes isolated from spleen and mRNA expression levels from distal parts of the colon were determined. Analysis of leukocytes isolated from the spleen of challenged NSG-UC mice corroborated CD64, CD163 and CD1a expressing CD14+ monocytes, CD1a expressing CD11b+ macrophages and HGF, TARC, IFNγ and TGFß1 mRNA as inflammatory markers. The disease network suggested that a proinflammatory condition elicited by IL-17c and lipids and relayed by cytotoxic T-cells, Th17 cells and CD1a expressing macrophages and monocytes. Conversely, the remodeling condition was evoked by IL-34 and TARC and promoted by Th2 cells and M2 monocytes. Mice benefitted from treatment with infliximab as indicated by the histological- and clinical score. As predicted by the disease network infliximab reduced the proinflammatory response by suppressing M1 monocytes and CD1a expressing monocytes and macrophages and decreased levels of IFNγ, TARC and HGF mRNA. As predicted by the disease network inflammation aggravated in the presence of pitrakinra as indicated by the clinical and histological score, elevated frequencies of CD1a expressing macrophages and TNFα and IFNγ mRNA levels. The combination of the disease network and the NSG-UC animal model might be developed into a powerful tool to predict efficacy or in-efficacy and potential mechanistic side effects.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 24%
Researcher 3 18%
Student > Bachelor 3 18%
Professor 2 12%
Unknown 5 29%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 3 18%
Medicine and Dentistry 2 12%
Psychology 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Neuroscience 1 6%
Other 1 6%
Unknown 8 47%
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 29 December 2017.
All research outputs
#18,581,651
of 23,015,156 outputs
Outputs from Journal of Translational Medicine
#2,977
of 4,025 outputs
Outputs of similar age
#330,004
of 441,975 outputs
Outputs of similar age from Journal of Translational Medicine
#59
of 61 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,025 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 17th percentile – i.e., 17% 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 441,975 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.