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Cited by 381

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

Silica-based nanoprobes for biomedical imaging and theranostic applications

Open access
Vivero-Escoto, Juan L., Huxford-Phillips, Rachel C., Lin, Wenbin·2012·Chemical Society Reviews

Abstract

Nanoparticle-based contrast agents are attracting a great deal of attention for various biomedical imaging and theranostic applications. Compared to conventional contrast agents, nanoparticles possess several potential advantages to improve in vivo detection and to enhance targeting efficiency. Silica-based nanoprobes can be engineered to achieve longer blood circulation times, specific clearance pathways, and multivalent binding. In this tutorial review, we summarize the latest progress on designing silica-based nanoprobes for imaging and theranostic applications. The synthesis of both solid silica and mesoporous silica nanoparticles is described, along with different approaches used for surface functionalization. Special emphasis is placed on the application of silica-based nanoprobes in optical, magnetic resonance, and multimodal imaging. The latest breakthroughs in the applications of silica nanoparticles as theranostic agents are also highlighted.

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Metadata

Authors
Vivero-Escoto, J. L., Huxford-Phillips, R. C., & Lin, W.
Venue
Chemical Society Reviews
Published
2012
Volume
41
Issue
7
Pages
2673
ISSN
  • 0306-0012 (ISSN-L)
  • 1460-4744
OpenAlex
W2057610600
Cited by
381
References
55
FWCI
3.95
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Silica-based nanoprobes for biomedical imaging and theranostic applications. https://app.cochat.ai/papers/10.1039/c2cs15229k
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Vivero-Escoto, J. L., Huxford-Phillips, R. C., & Lin, W. (2012). Silica-based nanoprobes for biomedical imaging and theranostic applications. Chemical Society Reviews. https://doi.org/10.1039/c2cs15229k

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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.