The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Targeting Strategies for Multifunctional Nanoparticles in Cancer Imaging and Therapy
Open accessAbstract
Nanomaterials offer new opportunities for cancer diagnosis and treatment. Multifunctional nanoparticles harboring various functions including targeting, imaging, therapy, and etc have been intensively studied aiming to overcome limitations associated with conventional cancer diagnosis and therapy. Of various nanoparticles, magnetic iron oxide nanoparticles with superparamagnetic property have shown potential as multifunctional nanoparticles for clinical translation because they have been used asmagnetic resonance imaging (MRI) constrast agents in clinic and their features could be easily tailored by including targeting moieties, fluorescence dyes, or therapeutic agents. This review summarizes targeting strategies for construction of multifunctional nanoparticles including magnetic nanoparticles-based theranostic systems, and the various surface engineering strategies of nanoparticles for in vivo applications.
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Cites
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Background
Cited by
Liposomes as nanomedical devices
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Advanced targeted therapies in cancer: Drug nanocarriers, the future of chemotherapy
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Therapeutic Nanoparticles and Their Targeted Delivery Applications
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Sol–gel based materials for biomedical applications
Owens, G. J., Singh, R. K., Foroutan, F., Alqaysi, M., Han, C.-M., Mahapatra, C., Kim, H.-W., & Knowles, J. C. (2016) · Progress in Materials Science · doi:10.1016/j.pmatsci.2015.12.001 · Cited by 958
Metadata
- Authors
- Yu, M. K., Park, J., & Jon, S.
- Venue
- Theranostics
- Publisher
- Ivyspring International Publisher
- Published
- 2012
- Volume
- 2
- Issue
- 1
- Pages
- 3-44
- ISSN
- 1838-7640 (ISSN-L)
- OpenAlex
- W2136633731
- Cited by
- 883
- References
- 12
- FWCI
- 29.58
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
