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The quest to make fully functional human pancreatic beta cells from embryonic stem cells: climbing a mountain in the clouds

Overview of attention for article published in Diabetologia, July 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

blogs
1 blog
twitter
32 X users

Citations

dimensions_citation
53 Dimensions

Readers on

mendeley
109 Mendeley
Title
The quest to make fully functional human pancreatic beta cells from embryonic stem cells: climbing a mountain in the clouds
Published in
Diabetologia, July 2016
DOI 10.1007/s00125-016-4059-4
Pubmed ID
Authors

James D. Johnson

Abstract

The production of fully functional insulin-secreting cells to treat diabetes is a major goal of regenerative medicine. In this article, I review progress towards this goal over the last 15 years from the perspective of a beta cell biologist. I describe the current state-of-the-art, and speculate on the general approaches that will be required to identify and achieve our ultimate goal of producing functional beta cells. The need for deeper phenotyping of heterogeneous cultures of stem cell derived islet-like cells in parallel with a better understanding of the heterogeneity of the target cell type(s) is emphasised. This deep phenotyping should include high-throughput single-cell analysis, as well as comprehensive 'omics technologies to provide unbiased characterisation of cell products and human beta cells. There are justified calls for more detailed and well-powered studies of primary human pancreatic beta cell physiology, and I propose online databases of standardised human beta cell responses to physiological stimuli, including both functional and metabolomic/proteomic/transcriptomic profiles. With a concerted, community-wide effort, including both basic and applied scientists, beta cell replacement will become a clinical reality for patients with diabetes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 32 X users 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 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 <1%
Unknown 108 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 28%
Researcher 27 25%
Student > Master 17 16%
Student > Bachelor 11 10%
Student > Doctoral Student 6 6%
Other 9 8%
Unknown 8 7%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 43 39%
Agricultural and Biological Sciences 31 28%
Medicine and Dentistry 13 12%
Engineering 4 4%
Pharmacology, Toxicology and Pharmaceutical Science 3 3%
Other 4 4%
Unknown 11 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 03 September 2019.
All research outputs
#1,496,857
of 25,732,188 outputs
Outputs from Diabetologia
#797
of 5,376 outputs
Outputs of similar age
#27,680
of 381,720 outputs
Outputs of similar age from Diabetologia
#19
of 82 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,376 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.7. This one has done well, scoring higher than 85% 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 381,720 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.