The DOI matches its Crossref record; 132 of the 132 references it cites were found in a registry or an index.
Applications of gold nanoparticles in cancer nanotechnology
Open accessAbstract
It has been almost 4 decades since the "war on cancer" was declared. It is now generally believed that personalized medicine is the future for cancer patient management. Possessing unprecedented potential for early detection, accurate diagnosis, and personalized treatment of cancer, nanoparticles have been extensively studied over the last decade. In this review, we will summarize the current state-of-the-art of gold nanoparticles in biomedical applications targeting cancer. Gold nanospheres, nanorods, nanoshells, nanocages, and surface enhanced Raman scattering nanoparticles will be discussed in detail regarding their uses in in vitro assays, ex vivo and in vivo imaging, cancer therapy, and drug delivery. Multifunctionality is the key feature of nanoparticle-based agents. Targeting ligands, imaging labels, therapeutic drugs, and other functionalities can all be integrated to allow for targeted molecular imaging and molecular therapy of cancer. Big strides have been made and many proof-of-principle studies have been successfully performed. The future looks brighter than ever yet many hurdles remain to be conquered. A multifunctional platform based on gold nanoparticles, with multiple receptor targeting, multimodality imaging, and multiple therapeutic entities, holds the promise for a "magic gold bullet" against cancer.
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A Review on the Synthesis and Functionalization of Gold Nanoparticles as a Drug Delivery Vehicle
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Metadata
- Authors
- Cai, W.
- Venue
- Nanotechnology, Science and Applications
- Publisher
- Informa UK Limited
- Published
- 2008-09
- Volume
- Volume 1
- Pages
- 17-32
- ISSN
- 1177-8903 (ISSN-L)
- OpenAlex
- W1832484719
- Cited by
- 851
- References
- 132
- FWCI
- 6.96
- Type
- journal article
- Language
- en
- Open access
- gold
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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.