| Title |
Aptamer-Functionalized Fluorescent Silica Nanoparticles for Highly Sensitive Detection of Leukemia Cells
|
|---|---|
| Published in |
Discover Nano, June 2016
|
| DOI | 10.1186/s11671-016-1512-8 |
| Pubmed ID | |
| Authors |
Juntao Tan, Nuo Yang, Zixi Hu, Jing Su, Jianhong Zhong, Yang Yang, Yating Yu, Jianmeng Zhu, Dabin Xue, Yingying Huang, Zongqiang Lai, Yong Huang, Xiaoling Lu, Yongxiang Zhao |
| Abstract |
A simple, highly sensitive method to detect leukemia cells has been developed based on aptamer-modified fluorescent silica nanoparticles (FSNPs). In this strategy, the amine-labeled Sgc8 aptamer was conjugated to carboxyl-modified FSNPs via amide coupling between amino and carboxyl groups. Sensitivity and specificity of Sgc8-FSNPs were assessed using flow cytometry and fluorescence microscopy. These results showed that Sgc8-FSNPs detected leukemia cells with high sensitivity and specificity. Aptamer-modified FSNPs hold promise for sensitive and specific detection of leukemia cells. Changing the aptamer may allow the FSNPs to detect other types of cancer cells. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 1% |
| Unknown | 67 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 21% |
| Student > Master | 12 | 18% |
| Other | 5 | 7% |
| Student > Bachelor | 5 | 7% |
| Researcher | 5 | 7% |
| Other | 5 | 7% |
| Unknown | 22 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 11 | 16% |
| Chemistry | 10 | 15% |
| Agricultural and Biological Sciences | 9 | 13% |
| Engineering | 7 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Other | 6 | 9% |
| Unknown | 22 | 32% |
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 15 June 2016.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from Discover Nano
#798
of 1,146 outputs
Outputs of similar age
#323,944
of 368,445 outputs
Outputs of similar age from Discover Nano
#23
of 29 outputs
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We're also able to compare this research output to 29 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.