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Cited by 366

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Stimuli‐Responsive NO Release for On‐Demand Gas‐Sensitized Synergistic Cancer Therapy

Fan, Wenpei, Yung, Bryant C., Chen, Xiaoyuan·2018·Angewandte Chemie International Edition

Abstract

Featuring high biocompatibility, the emerging field of gas therapy has attracted extensive attention in the medical and scientific communities. Currently, considerable research has focused on the gasotransmitter nitric oxide (NO) owing to its unparalleled dual roles in directly killing cancer cells at high concentrations and cooperatively sensitizing cancer cells to other treatments for synergistic therapy. Of particular note, recent state‐of‐the‐art studies have turned our attention to the chemical design of various endogenous/exogenous stimuli‐responsive NO‐releasing nanomedicines and their biomedical applications for on‐demand NO‐sensitized synergistic cancer therapy, which are discussed in this Minireview. Moreover, the potential challenges regarding NO gas therapy are also described, aiming to advance the development of NO nanomedicines as well as usher in new frontiers in this fertile research area.

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Crossref · 10.1002/anie.201800594

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Metadata

Authors
Fan, W., Yung, B. C., & Chen, X.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2018-05-08
Volume
57
Issue
28
Pages
8383-8394
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2789698994
Cited by
366
References
8
FWCI
13.31
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Stimuli‐Responsive NO Release for On‐Demand Gas‐Sensitized Synergistic Cancer Therapy. https://app.cochat.ai/papers/10.1002/anie.201800594
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Fan, W., Yung, B. C., & Chen, X. (2018). Stimuli‐Responsive NO Release for On‐Demand Gas‐Sensitized Synergistic Cancer Therapy. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201800594

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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.