The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.
More Effective Nanomedicines through Particle Design
Open accessAbstract
Nanomedicine is an emerging field that applies concepts in nanotechnology to develop novel diagnostics and therapies. Physical and chemical properties of particles, including size, shape, modulus, surface charge and surface chemistry, play an important role in determining particle–cell interactions, cellular trafficking mechanisms, biodistribution, and pharmacokinetics. This discussion focuses on both nanoparticles and microparticles since microparticles can also provide many insights for the development of drug carriers and possess advantages over nanoparticles in certain applications. This review covers recent major advancement in the nanomedicine field and also highlights studies using the PRINT technology.
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Cites
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Efficiency of siRNA delivery by lipid nanoparticles is limited by endocytic recycling
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Nanoparticle decoration with surfactants: Molecular interactions, assembly, and applications
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The resolution code of acute inflammation: Novel pro-resolving lipid mediators in resolution
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Polymeric Nanostructures for Imaging and Therapy
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Versatile Types of Organic/Inorganic Nanohybrids: From Strategic Design to Biomedical Applications
Zhao, N., Yan, L., Zhao, X., Chen, X., Li, A., Zheng, D., Zhou, X., Dai, X., & Xu, F.-J. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00401 · Cited by 429
Metadata
- Authors
- Wang, J., Byrne, J. D., Napier, M. E., & DeSimone, J. M.
- Venue
- Small
- Publisher
- Wiley
- Published
- 2011-06-22
- Volume
- 7
- Issue
- 14
- Pages
- 1919-1931
- ISSN
- 1613-6810 (ISSN-L)
- 1613-6829
- OpenAlex
- W2165031969
- Cited by
- 466
- References
- 135
- FWCI
- 15.31
- Type
- journal article
- Language
- en
- Open access
- green
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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.