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How to make insulin-producing pancreatic β cells for diabetes treatment

Overview of attention for article published in Science China Life Sciences, October 2016
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  • High Attention Score compared to outputs of the same age and source (90th percentile)

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1 policy source
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Citations

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20 Dimensions

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89 Mendeley
Title
How to make insulin-producing pancreatic β cells for diabetes treatment
Published in
Science China Life Sciences, October 2016
DOI 10.1007/s11427-016-0211-3
Pubmed ID
Authors

Jiaqi Lu, Qing Xia, Qiao Zhou

Abstract

Around 400 million people worldwide suffer from diabetes mellitus. The major pathological event for Type 1 diabetes and advanced Type 2 diabetes is loss or impairment of insulin-secreting β cells of the pancreas. For the past 100 years, daily insulin injection has served as a life-saving treatment for these patients. However, insulin injection often cannot achieve full glucose control, and over time poor glucose control leads to severe complications and mortality. As an alternative treatment, islet transplantation has been demonstrated to effectively maintain glucose homeostasis in diabetic patients, but its wide application is limited by the scarcity of donated islets. Therefore, it is important to define new strategies to obtain functional human β cells for transplantation therapies. Here, we summarize recent progress towards the production of β cells in vitro from pluripotent stem cells or somatic cell types including α cells, pancreatic exocrine cells, gastrointestinal stem cells, fibroblasts and hepatocytes. We also discuss novel methods for optimizing β cell transplantation and maintenance in vivo. From our perspective, the future of β cell replacement therapy is very promising although it is still challenging to control differentiation of β cells in vitro and to protect these cells from autoimmune attack in Type 1 diabetic patients. Overall, tremendous progress has been made in understanding β cell differentiation and producing functional β cells with different methods. In the coming years, we believe more clinical trials will be launched to move these technologies towards treatments to benefit diabetic patients.

X Demographics

X Demographics

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 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 1%
Unknown 88 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 20 22%
Student > Ph. D. Student 19 21%
Student > Master 12 13%
Researcher 9 10%
Student > Doctoral Student 3 3%
Other 10 11%
Unknown 16 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 26%
Agricultural and Biological Sciences 21 24%
Medicine and Dentistry 13 15%
Pharmacology, Toxicology and Pharmaceutical Science 5 6%
Engineering 2 2%
Other 6 7%
Unknown 19 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 June 2017.
All research outputs
#6,989,215
of 22,914,829 outputs
Outputs from Science China Life Sciences
#254
of 1,008 outputs
Outputs of similar age
#105,858
of 314,224 outputs
Outputs of similar age from Science China Life Sciences
#3
of 20 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,008 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one has gotten more attention than average, scoring higher than 74% of its peers.
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 314,224 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.