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Bioengineered three-dimensional diseased intervertebral disc model revealed inflammatory crosstalk

Overview of attention for article published in Clinical Materials, January 2017
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Title
Bioengineered three-dimensional diseased intervertebral disc model revealed inflammatory crosstalk
Published in
Clinical Materials, January 2017
DOI 10.1016/j.biomaterials.2017.01.045
Pubmed ID
Authors

Akshay Srivastava, Isma Liza Mohd Isa, Peadar Rooney, Abhay Pandit

Abstract

Without an appropriate disease model, the understanding of the pathophysiology of intervertebral disc degeneration and inflammation is limited. The lack of understanding limits the potential discovery of therapeutic targets as viable treatment options. Here, we report a versatile method to develop a three-dimensional intervertebral disc (IVD) model to study the response of nucleus pulposus (NP) and annulus fibrosus (AF) cells to inflammatory (IL-1β-induced) stimulation. The cell shape regulated IVD model was engineered by modulating the crosslinking of a self-assembled collagen hydrogel. The developed model has provided us with an understanding of the molecular changes that occur at genetic level which modulate the production of extracellular matrix components and key inflammatory pathways in the inflamed IVD. We have identified the role of the suppressor of cytokine proteins (SOCS) family in combating detrimental effects of pro-inflammatory cytokines in degenerated human NP tissue as predicted by the developed diseased model. The model could also provide an understanding of the expression of glycans implicated in the diseased IVD.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 15%
Researcher 9 15%
Student > Master 9 15%
Student > Bachelor 4 7%
Student > Postgraduate 3 5%
Other 9 15%
Unknown 18 30%
Readers by discipline Count As %
Engineering 12 20%
Medicine and Dentistry 6 10%
Materials Science 5 8%
Biochemistry, Genetics and Molecular Biology 4 7%
Agricultural and Biological Sciences 4 7%
Other 9 15%
Unknown 21 34%
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 26 February 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Clinical Materials
#10,081
of 10,751 outputs
Outputs of similar age
#365,096
of 424,113 outputs
Outputs of similar age from Clinical Materials
#118
of 129 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,751 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.