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One-step detection of circulating tumor cells in ovarian cancer using enhanced fluorescent silica nanoparticles

Overview of attention for article published in International Journal of Nanomedicine, June 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
1 news outlet
facebook
1 Facebook page

Citations

dimensions_citation
31 Dimensions

Readers on

mendeley
50 Mendeley
Title
One-step detection of circulating tumor cells in ovarian cancer using enhanced fluorescent silica nanoparticles
Published in
International Journal of Nanomedicine, June 2013
DOI 10.2147/ijn.s45059
Pubmed ID
Authors

Jin Hyun Kim, Hyun Hoon Chung, Min Sook Jeong, Mi Ryoung Song, Keon Wook Kang, Jun Sung Kim

Abstract

Ovarian cancer is the fifth-leading cause of cancer-related deaths among women as a result of late diagnosis. For survival rates to improve, more sensitive and specific methods for earlier detection of ovarian cancer are needed. This study presents the development of rapid and specific one-step circulating tumor cell (CTC) detection using flow cytometry in a whole-blood sample with fluorescent silica nanoparticles. We prepared magnetic nanoparticle (MNP)-SiO2(rhodamine B isothiocyanate [RITC]) (MNP-SiO2[RITC] incorporating organic dyes [RITC, ëmax(ex/em) = 543/580 nm]) in the silica shell. We then controlled the amount of organic dye in the silica shell of MNP-SiO2(RITC) for increased fluorescence intensity to overcome the autofluorescence of whole blood and increase the sensitivity of CTC detection in whole blood. Next, we modified the surface function group of MNP-SiO2(RITC) from -OH to polyethylene glycol (PEG)/COOH and conjugated a mucin 1 cell surface-associated (MUC1) antibody on the surface of MNP-SiO2(RITC) for CTC detection. To study the specific targeting efficiency of MUC1-MNP-SiO2(RITC), we used immunocytochemistry with a MUC1-positive human ovarian cancer cell line and a negative human embryonic kidney cell line. This technology was capable of detecting 100 ovarian cancer cells in 50 μL of whole blood. In conclusion, we developed a one-step CTC detection technology in ovarian cancer based on multifunctional silica nanoparticles and the use of flow cytometry.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 2%
Unknown 49 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 32%
Researcher 7 14%
Student > Master 5 10%
Student > Doctoral Student 4 8%
Student > Bachelor 3 6%
Other 6 12%
Unknown 9 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 26%
Medicine and Dentistry 9 18%
Chemistry 9 18%
Engineering 4 8%
Biochemistry, Genetics and Molecular Biology 3 6%
Other 0 0%
Unknown 12 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 28 November 2022.
All research outputs
#4,759,600
of 25,373,627 outputs
Outputs from International Journal of Nanomedicine
#368
of 4,123 outputs
Outputs of similar age
#38,631
of 206,481 outputs
Outputs of similar age from International Journal of Nanomedicine
#7
of 66 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,123 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 90% 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 206,481 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.