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Cited by 283

The DOI matches its Crossref record; 199 of the 199 references it cites were found in a registry or an index.

Targeting strategies for superparamagnetic iron oxide nanoparticles in cancer therapy

Zhi, Defu, Yang, Ting, Yang, Jian, Fu, Shuang, Zhang, Shubiao·2020·Acta Biomaterialia

Abstract

Among various nanoparticles, superparamagnetic iron oxide nanoparticles (SPIONs) have been increasingly studied for their excellent superparamagnetism, magnetic heating properties, and enhanced magnetic resonance imaging (MRI). The conjugation of SPIONs with drugs to obtain delivery nanosystems has several advantages including magnetic targeted functionalization, in vivo imaging, magnetic thermotherapy, and combined delivery of anticancer agents. To further increase the targeting efficiency of drugs through a delivery nanosystem based on SPIONs, additional targeting moieties including transferrin, antibodies, aptamers, hyaluronic acid, folate, and targeting peptides are coated onto the surface of SPIONs. Therefore, this review summarizes the latest progresses in the conjugation of targeting molecules and drug delivery nanosystems based on SPIONs, especially focusing on their performances to develop efficient targeted drug delivery systems for tumor therapy.

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Crossref · 10.1016/j.actbio.2019.11.027

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Metadata

Authors
Zhi, D., Yang, T., Yang, J., Fu, S., & Zhang, S.
Venue
Acta Biomaterialia
Publisher
Elsevier BV
Published
2020-01
Volume
102
Pages
13-34
ISSN
1742-7061 (ISSN-L)
OpenAlex
W2990574737
Cited by
283
References
199
FWCI
6.32
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Targeting strategies for superparamagnetic iron oxide nanoparticles in cancer therapy. https://app.cochat.ai/papers/10.1016/j.actbio.2019.11.027
The paper
Zhi, D., Yang, T., Yang, J., Fu, S., & Zhang, S. (2020). Targeting strategies for superparamagnetic iron oxide nanoparticles in cancer therapy. Acta Biomaterialia. https://doi.org/10.1016/j.actbio.2019.11.027

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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.