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Cited by 364

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Reactive Oxygen Species (ROS) Responsive Polymers for Biomedical Applications

Open access
Xu, Qinghua, He, Chaoliang, Xiao, Chunsheng, Chen, Xuesi·2016·Macromolecular Bioscience

Abstract

Reactive oxygen species (ROS) play important roles in cell signaling pathways, while increased production of ROS may disrupt cellular homeostasis, giving rise to oxidative stress and a series of diseases. Utilizing these cell‐generated species as triggers for selective tuning polymer structures and properties represents a promising methodology for disease diagnosis and treatment. Recently, significant progress has been made in fabricating biomaterials including nanoparticles and macroscopic networks to interact with this dynamic physiological condition. These ROS‐responsive platforms have shown potential in a range of biomedical applications, such as cancer targeted drug delivery systems, cell therapy platforms for inflammation related disease, and so on. image

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Crossref · 10.1002/mabi.201500440

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Metadata

Authors
Xu, Q., He, C., Xiao, C., & Chen, X.
Venue
Macromolecular Bioscience
Publisher
Wiley
Published
2016-02-18
Volume
16
Issue
5
Pages
635-646
ISSN
  • 1616-5187 (ISSN-L)
  • 1616-5195
OpenAlex
W2280162925
Cited by
364
References
2
FWCI
15.46
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Reactive Oxygen Species (ROS) Responsive Polymers for Biomedical Applications. https://app.cochat.ai/papers/10.1002/mabi.201500440
The paper
Xu, Q., He, C., Xiao, C., & Chen, X. (2016). Reactive Oxygen Species (ROS) Responsive Polymers for Biomedical Applications. Macromolecular Bioscience. https://doi.org/10.1002/mabi.201500440

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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.