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Self-Assembled Superparamagnetic Iron Oxide Nanoclusters for Universal Cell Labeling and MRI

Overview of attention for article published in Discover Nano, May 2016
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Title
Self-Assembled Superparamagnetic Iron Oxide Nanoclusters for Universal Cell Labeling and MRI
Published in
Discover Nano, May 2016
DOI 10.1186/s11671-016-1479-5
Pubmed ID
Authors

Shuzhen Chen, Jun Zhang, Shengwei Jiang, Gan Lin, Bing Luo, Huan Yao, Yuchun Lin, Chengyong He, Gang Liu, Zhongning Lin

Abstract

Superparamagnetic iron oxide (SPIO) nanoparticles have been widely used in a variety of biomedical applications, especially as contrast agents for magnetic resonance imaging (MRI) and cell labeling. In this study, SPIO nanoparticles were stabilized with amphiphilic low molecular weight polyethylenimine (PEI) in an aqueous phase to form monodispersed nanocomposites with a controlled clustering structure. The iron-based nanoclusters with a size of 115.3 ± 40.23 nm showed excellent performance on cellular uptake and cell labeling in different types of cells, moreover, which could be tracked by MRI with high sensitivity. The SPIO nanoclusters presented negligible cytotoxicity in various types of cells as detected using MTS, LDH, and flow cytometry assays. Significantly, we found that ferritin protein played an essential role in protecting stress from SPIO nanoclusters. Taken together, the self-assembly of SPIO nanoclusters with good magnetic properties provides a safe and efficient method for universal cell labeling with noninvasive MRI monitoring capability.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 32%
Other 2 6%
Student > Master 2 6%
Student > Bachelor 2 6%
Researcher 2 6%
Other 2 6%
Unknown 11 35%
Readers by discipline Count As %
Medicine and Dentistry 4 13%
Materials Science 4 13%
Chemistry 4 13%
Biochemistry, Genetics and Molecular Biology 3 10%
Physics and Astronomy 2 6%
Other 4 13%
Unknown 10 32%