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Circulating unmethylated insulin DNA as a potential non-invasive biomarker of beta cell death in type 1 Diabetes: a review and future prospect

Overview of attention for article published in Clinical Epigenetics, April 2017
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Title
Circulating unmethylated insulin DNA as a potential non-invasive biomarker of beta cell death in type 1 Diabetes: a review and future prospect
Published in
Clinical Epigenetics, April 2017
DOI 10.1186/s13148-017-0343-5
Pubmed ID
Authors

Kuo Zhang, Guigao Lin, Yanxi Han, Jiehong Xie, Jinming Li

Abstract

The early detection of type 1 diabetes (T1D) largely depends on a reliable approach to monitor β cell loss. An effective way to evaluate the decline of β cell mass would allow early preventative intervention to preserve insulin secretion. Recent progress in the development of novel biomarkers, based on tissue-specific methylation patterns, has inspired relevant studies in T1D. In this review, we focus on the application of circulating β cell-derived unmethylated insulin (INS) DNA. Circulating β cell-derived unmethylated INS DNA has a potential clinical value for the early detection of T1D, surveillance of islet transplantation rejection, and evaluation of response to therapy. Utilizing differentiated methylation patterns in different organs and employing a wide variety of molecular technologies also provide insights into the interrogation of biomarkers in other diseases with massive tissue-specific cell loss. Circulating unmethylated INS DNA is a promising molecular biomarker for the early detection of T1D.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 17%
Student > Bachelor 10 16%
Student > Ph. D. Student 9 14%
Other 4 6%
Student > Master 4 6%
Other 6 10%
Unknown 19 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 19%
Medicine and Dentistry 9 14%
Agricultural and Biological Sciences 7 11%
Nursing and Health Professions 3 5%
Immunology and Microbiology 3 5%
Other 7 11%
Unknown 22 35%
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 April 2017.
All research outputs
#17,890,958
of 22,968,808 outputs
Outputs from Clinical Epigenetics
#946
of 1,261 outputs
Outputs of similar age
#220,631
of 309,828 outputs
Outputs of similar age from Clinical Epigenetics
#22
of 34 outputs
Altmetric has tracked 22,968,808 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,261 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one is in the 20th percentile – i.e., 20% 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 309,828 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.