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Mendeley readers
Attention Score in Context
| Title |
Aurora kinase A induces miR-17-92 cluster through regulation of E2F1 transcription factor
|
|---|---|
| Published in |
Cellular and Molecular Life Sciences, March 2010
|
| DOI | 10.1007/s00018-010-0340-8 |
| Pubmed ID | |
| Authors |
Shun He, Shangbin Yang, Guohua Deng, Mei Liu, Hongxia Zhu, Wei Zhang, Shuang Yan, Lanping Quan, Jinfeng Bai, Ningzhi Xu |
| Abstract |
Aurora kinase A (AURKA) is an essential mitotic serine/threonine kinase and its abnormal expression is observed in many malignancies, yet the exact role for AURKA in tumorigenesis still remains elusive. Here, through a transcription factor array, we show that the transcription activity of E2F1 was increased by AURKA overexpression. Meanwhile, the E2F1 protein level was found to be upregulated and a correlation between AURKA and E2F1 expression was observed in cancer specimens. Further analysis revealed that AURKA increased E2F1 protein stability by inhibiting proteasome-dependent degradation of this protein. Additionally, a microRNA cluster, miR-17-92, was found to be upregulated upon AURKA overexpression, and this stimulation was largely repressed by E2F1 knockdown. Chromatin immunoprecipitation further demonstrated that AURKA enhanced E2F1 occupancy to the promoter of the miR-17-92 cluster. These data reveal a novel link between AURKA and microRNAs via the regulation of E2F1, providing new clues for understanding the role of AURKA in tumorigenesis. |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 3% |
| France | 1 | 3% |
| Austria | 1 | 3% |
| Unknown | 31 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 35% |
| Researcher | 10 | 29% |
| Student > Master | 5 | 15% |
| Professor > Associate Professor | 2 | 6% |
| Professor | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 2 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 65% |
| Biochemistry, Genetics and Molecular Biology | 4 | 12% |
| Medicine and Dentistry | 3 | 9% |
| Computer Science | 1 | 3% |
| Neuroscience | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 2 | 6% |
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 20 November 2010.
All research outputs
#7,845,540
of 23,794,258 outputs
Outputs from Cellular and Molecular Life Sciences
#1,655
of 4,151 outputs
Outputs of similar age
#35,470
of 96,260 outputs
Outputs of similar age from Cellular and Molecular Life Sciences
#13
of 26 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,151 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 38th percentile – i.e., 38% 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 96,260 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.