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Cited by 1,951

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Chemodynamic Therapy: Tumour Microenvironment‐Mediated Fenton and Fenton‐like Reactions

Tang, Zhongmin, Liu, Yanyan, He, Mingyuan, Bu, Wenbo·2019·Angewandte Chemie International Edition

Abstract

Tailored to the specific tumour microenvironment, which involves acidity and the overproduction of hydrogen peroxide, advanced nanotechnology has been introduced to generate the hydroxyl radical (.OH) primarily for tumour chemodynamic therapy (CDT) through the Fenton and Fenton‐like reactions. Numerous studies have investigated the enhancement of CDT efficiency, primarily the increase in the amount of .OH generated. Notably, various strategies based on the Fenton reaction have been employed to enhance .OH generation, including nanomaterials selection, modulation of the reaction environment, and external energy fields stimulation, which are discussed systematically in this Minireview. Furthermore, the potential challenges and the methods used to facilitate CDT effectiveness are also presented to support this cutting‐edge research area.

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Metadata

Authors
Tang, Z., Liu, Y., He, M., & Bu, W.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2018-11-20
Volume
58
Issue
4
Pages
946-956
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2883440571
Cited by
1,951
References
6
FWCI
62.48
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Chemodynamic Therapy: Tumour Microenvironment‐Mediated Fenton and Fenton‐like Reactions. https://app.cochat.ai/papers/10.1002/anie.201805664
The paper
Tang, Z., Liu, Y., He, M., & Bu, W. (2019). Chemodynamic Therapy: Tumour Microenvironment‐Mediated Fenton and Fenton‐like Reactions. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201805664

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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.