↓ Skip to main content

MicroRNA, Proteins, and Metabolites as Novel Biomarkers for Prediabetes, Diabetes, and Related Complications

Overview of attention for article published in Frontiers in endocrinology, April 2018
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
114 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
MicroRNA, Proteins, and Metabolites as Novel Biomarkers for Prediabetes, Diabetes, and Related Complications
Published in
Frontiers in endocrinology, April 2018
DOI 10.3389/fendo.2018.00180
Pubmed ID
Authors

Suniti Vaishya, Rucha D. Sarwade, Vasudevan Seshadri

Abstract

Type 2 diabetes mellitus (T2DM) is no more a lifestyle disease of developed countries. It has emerged as a major health problem worldwide including developing countries. However, how diabetes could be detected at an early stage (prediabetes) to prevent the progression of disease is still unclear. Currently used biomarkers like glycated hemoglobin and assessment of blood glucose level have their own limitations. These classical markers can be detected when the disease is already established. Prognosis of disease at early stages and prediction of population at a higher risk require identification of specific markers that are sensitive enough to be detected at early stages of disease. Biomarkers which could predict the risk of disease in people will be useful for developing preventive/proactive therapies to those individuals who are at a higher risk of developing the disease. Recent studies suggested that the expression of biomolecules including microRNAs, proteins, and metabolites specifically change during the progression of T2DM and related complications, suggestive of disease pathology. Owing to their omnipresence in body fluids and their association with onset, progression, and pathogenesis of T2DM, these biomolecules can be potential biomarker for prognosis, diagnosis, and management of disease. In this article, we summarize biomolecules that could be potential biomarkers and their signature changes associated with T2DM and related complications during disease pathogenesis.

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

Geographical breakdown

Country Count As %
Unknown 114 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 15%
Student > Master 17 15%
Student > Bachelor 10 9%
Professor > Associate Professor 8 7%
Researcher 7 6%
Other 20 18%
Unknown 35 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 26%
Medicine and Dentistry 13 11%
Agricultural and Biological Sciences 8 7%
Nursing and Health Professions 7 6%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Other 14 12%
Unknown 38 33%
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 24 April 2018.
All research outputs
#22,945,287
of 25,584,565 outputs
Outputs from Frontiers in endocrinology
#8,469
of 13,236 outputs
Outputs of similar age
#300,362
of 340,561 outputs
Outputs of similar age from Frontiers in endocrinology
#171
of 229 outputs
Altmetric has tracked 25,584,565 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,236 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 1st percentile – i.e., 1% 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 340,561 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 229 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.