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Challenges to Reshape the Future of Type 1 Diabetes Research

Overview of attention for article published in JCEM, June 2018
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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 (80th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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16 X users

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35 Mendeley
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Article details
Title
Challenges to Reshape the Future of Type 1 Diabetes Research
Published in
JCEM, June 2018
DOI 10.1210/jc.2018-00568
Pubmed ID
Authors
Abstract

Immunotherapy trials to prevent type 1 diabetes have been unsuccessful for more than fifteen years. Understanding pitfalls and knowledge gaps in the immunology of type 1 diabetes should lead us in new directions that will yield better trial outcomes. A proposal is made for precision medicine trial design in future type 1 diabetes studies. High quality peer-reviewed basic science and clinical research trials for type 1 diabetes were used in this Perspectives article. Type 1 diabetes publications were reviewed from the years 2000 to 2018 using Google Scholar and PubMed reference databases. Personalized medicine for type 1 diabetes should recognize that each individual has phenotypic and genotypic quirks that distinguish them from other study subjects. A uniform protocol for antigen-specific immunotherapy has consistently failed to prevent disease. An alternative approach using molecular tools to personalize the preventive treatment strategy might be a road forward for type 1 diabetes research. Assumptions or lack knowledge about disease stratification (not all type 1 diabetes is the same disease), individualized antigen-specific T-cells, regulatory T-cell populations, and T-cell receptor rearrangement are just a few aspects of immunology that need integration with clinical trial design. The type 1 diabetes research community continues to bring forward novel immunotherapy trials to prevent disease, but this approach is unlikely to succeed until several fundamental aspects of clinical immunology are recognized and addressed. Here, we identify several knowledge gaps that could rectify type 1 diabetes trial design and lead to future success.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 5 14%
Student > Ph. D. Student 4 11%
Student > Master 3 9%
Student > Doctoral Student 2 6%
Researcher 2 6%
Other 3 9%
Unknown 16 46%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 14%
Medicine and Dentistry 4 11%
Nursing and Health Professions 3 9%
Immunology and Microbiology 3 9%
Agricultural and Biological Sciences 2 6%
Other 2 6%
Unknown 16 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 18 August 2018.
All research outputs
#4,982,012
of 34,763,505 outputs
Outputs from JCEM
#5,040
of 21,239 outputs
Outputs of similar age
#72,983
of 374,691 outputs
Outputs of similar age from JCEM
#45
of 120 outputs
Altmetric has tracked 34,763,505 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 21,239 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.9. This one has done well, scoring higher than 75% 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 374,691 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.