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Cited by 396

The DOI matches its Crossref record; 117 of the 117 references it cites were found in a registry or an index.

Plant-derived exosome-like nanoparticles and their therapeutic activities

Open access
Kim, Jisu, Li, Shiyi, Zhang, Shuya, Wang, Jianxin·2022·Asian Journal of Pharmaceutical Sciences

Abstract

Nanotechnologies have been successfully applied to the treatment of various diseases. Plant-derived exosome-like nanoparticles (PENs) are expected to become effective therapeutic modalities for treating disease or in drug-delivery. PENs are minimally cytotoxic to healthy tissues, with which they show excellent biocompatibility, and are biased towards tumors by targeting specific tissues through special endocytosis mechanisms. Thus, the use of these PENs may expand the scope of drug therapies while reducing the off-target effects. In this review, we summarize the fundamental features and bioactivities of PENs extracted from the grape, grapefruit, ginger, lemon, and broccoli and discuss the applications of these particles as therapeutics and nanocarriers.

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Crossref · 10.1016/j.ajps.2021.05.006

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Metadata

Authors
Kim, J., Li, S., Zhang, S., & Wang, J.
Venue
Asian Journal of Pharmaceutical Sciences
Publisher
Elsevier BV
Published
2022-01
Volume
17
Issue
1
Pages
53-69
ISSN
1818-0876 (ISSN-L)
OpenAlex
W3177909407
Cited by
396
References
117
FWCI
13.22
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Plant-derived exosome-like nanoparticles and their therapeutic activities. https://app.cochat.ai/papers/10.1016/j.ajps.2021.05.006
The paper
Kim, J., Li, S., Zhang, S., & Wang, J. (2022). Plant-derived exosome-like nanoparticles and their therapeutic activities. Asian Journal of Pharmaceutical Sciences. https://doi.org/10.1016/j.ajps.2021.05.006

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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.