↓ Skip to main content

Estimating the survival advantage based on telomere length and serum biomarkers of aging

Overview of attention for article published in Journal of Translational Medicine, August 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
22 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
Estimating the survival advantage based on telomere length and serum biomarkers of aging
Published in
Journal of Translational Medicine, August 2017
DOI 10.1186/s12967-017-1267-8
Pubmed ID
Authors

Yilin Zhao, Shijun Li, Hui Liu

Abstract

This study aimed to establish a model that estimates the survival advantage at the molecular level based on telomere length and serum biomarkers of aging, to explore clinical significance. The study consisted of 100 healthy subjects and 40 type 2 diabetes mellitus patients, 20-90 years of age. Saliva telomere relative length (LnTL) was measured by the quantitative real-time polymerase chain reaction and the serum biochemical parameters, including albumin (ALB), total proteins, total cholesterol, triglycerides, and some enzyme parameters were detected by a biochemical analyzer. The Z values were transformed from mean values and standard deviations to estimate the survival advantage. A normal reference range (95% confidence interval) was set to the comprehensive advantage of the Z values (Zs) to evaluate the comprehensive survival advantage. The Z values of serum ALB and saliva LnTL could be used to estimate the survival advantage, and effectively distinguish between the aging and nonaging individuals. The Zs was greater than 1.64 in the normal reference range, and type 2 diabetes mellitus patients had lower survival advantages compared to those of the control group (p < 0.05). Our two-dimensional model system using ALB and LnTL was valid and may have potential applications for evaluating the aging status at the molecular level, and for the observation of disease characteristics.

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

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 18%
Student > Master 2 9%
Professor > Associate Professor 2 9%
Student > Ph. D. Student 2 9%
Researcher 2 9%
Other 2 9%
Unknown 8 36%
Readers by discipline Count As %
Medicine and Dentistry 4 18%
Biochemistry, Genetics and Molecular Biology 2 9%
Agricultural and Biological Sciences 2 9%
Economics, Econometrics and Finance 1 5%
Nursing and Health Professions 1 5%
Other 2 9%
Unknown 10 45%
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 01 August 2017.
All research outputs
#20,441,465
of 22,996,001 outputs
Outputs from Journal of Translational Medicine
#3,334
of 4,019 outputs
Outputs of similar age
#276,934
of 317,441 outputs
Outputs of similar age from Journal of Translational Medicine
#49
of 54 outputs
Altmetric has tracked 22,996,001 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 4,019 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. 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 317,441 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 54 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.