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miR-130a can predict response to temozolomide in patients with glioblastoma multiforme, independently of O6-methylguanine-DNA methyltransferase

Overview of attention for article published in Journal of Translational Medicine, January 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
5 tweeters

Citations

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24 Dimensions

Readers on

mendeley
32 Mendeley
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Title
miR-130a can predict response to temozolomide in patients with glioblastoma multiforme, independently of O6-methylguanine-DNA methyltransferase
Published in
Journal of Translational Medicine, January 2015
DOI 10.1186/s12967-015-0435-y
Pubmed ID
Authors

Huiyuan Chen, Xinyi Li, Wenbin Li, Huyong Zheng

Abstract

Currently, O6-methylguanine-DNA methyltransferase(MGMT) promoter methylation is the most convincing predictive biomarker for temozolomide (TMZ) response in patients with glioblastoma multiforme (GBM). However, technical obstacles prevent this biomarker from being applied widely. On the other hand, microRNAs (miRNAs) are easily investigated in the clinical setting using quantitative real-time polymerase chain reactions. This study aimed to identify miRNAs that could serve as predictive biomarkers for TMZ response.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 25%
Student > Ph. D. Student 6 19%
Student > Master 6 19%
Other 3 9%
Student > Postgraduate 2 6%
Other 4 13%
Unknown 3 9%
Readers by discipline Count As %
Medicine and Dentistry 10 31%
Biochemistry, Genetics and Molecular Biology 8 25%
Agricultural and Biological Sciences 7 22%
Business, Management and Accounting 1 3%
Unknown 6 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 25 April 2015.
All research outputs
#6,509,504
of 12,299,747 outputs
Outputs from Journal of Translational Medicine
#829
of 2,402 outputs
Outputs of similar age
#86,673
of 225,156 outputs
Outputs of similar age from Journal of Translational Medicine
#33
of 109 outputs
Altmetric has tracked 12,299,747 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,402 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has gotten more attention than average, scoring higher than 63% 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 225,156 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 109 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 66% of its contemporaries.