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Detection of Cystatin C biomarker for clinical measurement of renal disease by developed ELISA diagnostic kits

Overview of attention for article published in Journal of Translational Medicine, September 2014
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Title
Detection of Cystatin C biomarker for clinical measurement of renal disease by developed ELISA diagnostic kits
Published in
Journal of Translational Medicine, September 2014
DOI 10.1186/1479-5876-12-205
Pubmed ID
Authors

Renren Jiang, Chao Xu, Xiaoli Zhou, Tianhao Wang, Gang Yao

Abstract

Human cystatin C (HCC) is a potential biomarker for tubular damage and impaired renal function. It is difficult to obtain efficient paired monoclonal antibodies against HCC with low molecular to meet the requirements for clinical application The present study was to establish a stable and repeatable measurement for HCC with self-made monoclonal antibodies (McAbs) and Variable domain of heavy chain of heavy-chain antibody (VHHs) increase the sensitivity.

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

Geographical breakdown

Country Count As %
Algeria 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 19%
Student > Ph. D. Student 6 17%
Student > Bachelor 5 14%
Student > Doctoral Student 3 8%
Student > Master 2 6%
Other 4 11%
Unknown 9 25%
Readers by discipline Count As %
Medicine and Dentistry 4 11%
Agricultural and Biological Sciences 4 11%
Biochemistry, Genetics and Molecular Biology 3 8%
Chemistry 3 8%
Veterinary Science and Veterinary Medicine 2 6%
Other 7 19%
Unknown 13 36%
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 12 September 2014.
All research outputs
#22,051,351
of 24,602,766 outputs
Outputs from Journal of Translational Medicine
#3,699
of 4,426 outputs
Outputs of similar age
#211,890
of 248,661 outputs
Outputs of similar age from Journal of Translational Medicine
#62
of 81 outputs
Altmetric has tracked 24,602,766 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 4,426 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. 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 248,661 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 81 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.