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Biocompatibility of Mesoporous Silica Nanoparticles
Abstract
In this review, recent reports on the biocompatibility of mesoporous silica nanoparticles (MSNs) are reviewed, with special emphasis being paid to the correlations between MSNs' structural and compositional features and their biological effects on various cells and tissues. First, the different synthetic routes used to produce the most common types of MSNs and the various methods employed to functionalize their surfaces are discussed. This is, however, done only briefly because of the focus of the review being the biocompatibility of the materials. Similarly, the biological applications of MSNs in areas such as drug and gene delivery, biocatalysis, bioimaging, and biosensing are briefly introduced. Many examples have also been mentioned about the biological applications of MSNs while discussing the materials' biocompatibility. The cytotoxicity of different types of MSNs and the effects of their various structural characteristics on their biological activities, which are the focus of this review, are then described in detail. In addition, synthetic strategies developed to reduce or eliminate any possible negative biological effects associated with MSNs or to improve their biocompatibility, as necessary, are illustrated. At the same time, recent reports on the interactions between MSNs and various in vivo or in vitro biological systems, plus our opinions and remarks on what the future may hold for this field, are included.
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Metadata
- Authors
- Asefa, T., & Tao, Z.
- Venue
- Chemical Research in Toxicology
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-08-10
- Volume
- 25
- Issue
- 11
- Pages
- 2265-2284
- ISSN
- 0893-228X (ISSN-L)
- 1520-5010
- OpenAlex
- W2024483368
- Cited by
- 422
- References
- 109
- FWCI
- 10.43
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
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.