The DOI matches its Crossref record; 124 of the 124 references it cites were found in a registry or an index.
Red blood cell membrane-camouflaged nanoparticles: a novel drug delivery system for antitumor application
Open accessAbstract
Erythrocytes (red blood cells, RBCs) are the most abundant circulating cells in the blood and have been widely used in drug delivery systems (DDS) because of their features of biocompatibility, biodegradability, and long circulating half-life. Accordingly, a "camouflage" comprised of erythrocyte membranes renders nanoparticles as a platform that combines the advantages of native erythrocyte membranes with those of nanomaterials. Following injection into the blood of animal models, the coated nanoparticles imitate RBCs and interact with the surroundings to achieve long-term circulation. In this review, the biomimetic platform of erythrocyte membrane-coated nano-cores is described with regard to various aspects, with particular focus placed on the coating mechanism, preparation methods, verification methods, and the latest anti-tumor applications. Finally, further functional modifications of the erythrocyte membranes and attempts to fuse the surface properties of multiple cell membranes are discussed, providing a foundation to stimulate extensive research into multifunctional nano-biomimetic systems.
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Immune Cell Membrane‐Coated Biomimetic Nanoparticles for Targeted Cancer Therapy
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Metadata
- Authors
- Xia, Q., Zhang, Y., Li, Z., Hou, X., & Feng, N.
- Venue
- Acta Pharmaceutica Sinica B
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 9
- Issue
- 4
- Pages
- 675-689
- ISSN
- 2211-3835 (ISSN-L)
- OpenAlex
- W2912471195
- Cited by
- 665
- References
- 124
- FWCI
- 14.47
- Type
- journal article
- Language
- en
- Open access
- gold
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- Xia, Q., Zhang, Y., Li, Z., Hou, X., & Feng, N. (2019). Red blood cell membrane-camouflaged nanoparticles: a novel drug delivery system for antitumor application. Acta Pharmaceutica Sinica B. https://doi.org/10.1016/j.apsb.2019.01.011
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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