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Understanding the regulation of pattern recognition receptors in inflammatory diseases - a ‘Nod’ in the right direction

Overview of attention for article published in Immunology, November 2016
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1 tweeter

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Title
Understanding the regulation of pattern recognition receptors in inflammatory diseases - a ‘Nod’ in the right direction
Published in
Immunology, November 2016
DOI 10.1111/imm.12677
Pubmed ID
Authors

Claire L. Feerick, Declan P. McKernan

Abstract

NOD-like receptors (NLRs) are a family of 23 receptors known as pattern recognition receptors (PRRs), they are expressed in many cell types and play a key role in the innate immune response. The NLRs are activated by pathogen associated molecular patterns (PAMPs) which include structurally conserved molecules present on the surfaces of bacteria. The activation of these NLRs by pathogens results in the downstream activation of signalling kinases and transcription factors, culminating in the transcription of genes coding for pro-inflammatory factors. NLR expression is altered in many cellular, physiological and disease states. There is a lack of understanding of the mechanisms by which NLR expression is regulated, particularly in chronic inflammatory states. Genetic polymorphisms and protein interactions are included in such mechanisms. This review seeks to examine the current knowledge regarding the regulation of this family of receptors and their signalling pathways as well as how their expression changes in disease states with particular focus on NOD1 and NOD2 in inflammatory bowel diseases amongst others. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Turkey 1 2%
Unknown 41 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 21%
Student > Bachelor 8 19%
Student > Master 7 17%
Student > Doctoral Student 5 12%
Researcher 4 10%
Other 9 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 33%
Immunology and Microbiology 7 17%
Biochemistry, Genetics and Molecular Biology 7 17%
Medicine and Dentistry 6 14%
Unspecified 5 12%
Other 3 7%

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 06 October 2016.
All research outputs
#9,860,951
of 12,348,212 outputs
Outputs from Immunology
#1,566
of 1,817 outputs
Outputs of similar age
#186,567
of 266,388 outputs
Outputs of similar age from Immunology
#27
of 36 outputs
Altmetric has tracked 12,348,212 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 1,817 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 7th percentile – i.e., 7% 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 266,388 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.