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Nanosilver particles in medical applications: synthesis, performance, and toxicity

Open access
Xing, Malcolm, Ge, Liangpeng, Wang, Meng, Li, Qingtao, Li, Xiojian, Ouyang, Jun·2014·International Journal of Nanomedicine

Abstract

Nanosilver particles (NSPs), are among the most attractive nanomaterials, and have been widely used in a range of biomedical applications, including diagnosis, treatment, drug delivery, medical device coating, and for personal health care. With the increasing application of NSPs in medical contexts, it is becoming necessary for a better understanding of the mechanisms of NSPs' biological interactions and their potential toxicity. In this review, we first introduce the synthesis routes of NSPs, including physical, chemical, and biological or green synthesis. Then the unique physiochemical properties of NSPs, such as antibacterial, antifungal, antiviral, and anti-inflammatory activity, are discussed in detail. Further, some recent applications of NSPs in prevention, diagnosis, and treatment in medical fields are described. Finally, potential toxicology considerations of NSPs, both in vitro and in vivo, are also addressed.

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Metadata

Authors
Xing, M., Ge, L., Wang, M., Li, Q., Li, X., & Ouyang, J.
Venue
International Journal of Nanomedicine
Published
2014-05
Volume
9
Pages
2399
ISSN
  • 1176-9114 (ISSN-L)
  • 1178-2013
OpenAlex
W1991590198
Cited by
582
References
2
FWCI
20.25
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Nanosilver particles in medical applications: synthesis, performance, and toxicity. https://app.cochat.ai/papers/10.2147/ijn.s55015
The paper
Xing, M., Ge, L., Wang, M., Li, Q., Li, X., & Ouyang, J. (2014). Nanosilver particles in medical applications: synthesis, performance, and toxicity. International Journal of Nanomedicine. https://doi.org/10.2147/ijn.s55015

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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.