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SP1 and UTE1 Decoy ODNs inhibit activation and proliferation of hepatic stellate cells by targeting tissue inhibitors of metalloproteinase 1

Overview of attention for article published in Cell & Bioscience, May 2016
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Title
SP1 and UTE1 Decoy ODNs inhibit activation and proliferation of hepatic stellate cells by targeting tissue inhibitors of metalloproteinase 1
Published in
Cell & Bioscience, May 2016
DOI 10.1186/s13578-016-0094-6
Pubmed ID
Authors

Dong Jia, Yi-Ran Ni, Yan-Qiong Zhang, Chun Rao, Jun Hou, He-Qing Tang, Chang-Bai Liu, Jiang-Feng Wu

Abstract

The excessive accumulation of extracellular matrix of hepatic fibrosis is positively correlated with tissue inhibitors of metalloproteinase 1 (TIMP1). Here we aimed to investigate whether TIMP1 may be down-regulated by Decoy ODNs strategy to capture transcriptional factor upstream TIMP1 element 1 (UTE1) and specificity protein 1(SP1). By luciferase reporter assays, we confirmed that these Decoy ODNs could influence the promoter activation of TIMP-1, α-SMA and Collagen Iα2 (COLΙα2) genes as well as the enhancer activation of TRE in HSC-T6 cells, and the combination tended to be more effective than SP1 or UTE1 Decoy ODN alone. Western blot analysis also demonstrated down-regulation of the expression of those target genes except for TGF-β. Furthermore, we observed that the viability of HSC-T6 cells at 72 h was significantly in decline in combination group. The combination of SP1 and UTE1 Decoy ODNs treatments inhibit the activation and proliferation of HSCs more effectively than one of the Decoy ODNs through co-regulation of TIMP1 and TGF-β signal pathway but not the expression of TGF-β itself.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 18%
Student > Ph. D. Student 2 18%
Researcher 2 18%
Student > Master 1 9%
Professor 1 9%
Other 0 0%
Unknown 3 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 27%
Biochemistry, Genetics and Molecular Biology 2 18%
Immunology and Microbiology 1 9%
Engineering 1 9%
Unknown 4 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 10 May 2016.
All research outputs
#18,456,836
of 22,869,263 outputs
Outputs from Cell & Bioscience
#563
of 934 outputs
Outputs of similar age
#224,347
of 304,990 outputs
Outputs of similar age from Cell & Bioscience
#13
of 20 outputs
Altmetric has tracked 22,869,263 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 934 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 12th percentile – i.e., 12% 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 304,990 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.