The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Enhanced Generation of Non-Oxygen Dependent Free Radicals by Schottky-type Heterostructures of Au–Bi2S3 Nanoparticles via X-ray-Induced Catalytic Reaction for Radiosensitization
Abstract
Despite the development of nanomaterials with high-Z elements for radiosensitizers, most of them suffer from their oxygen-dependent behavior in hypoxic tumor, nonideal selectivity to tumor, or inevasible damages to normal tissue, greatly limiting their further applications. Herein, we develop a Schottky-type heterostructure of Au–Bi2S3 with promising ability of reactive free radicals generation under X-ray irradiation for selectively enhancing radiotherapeutic efficacy by catalyzing intracellular H2O2 in tumor. On the one hand, like many other nanomaterials with rich high-Z elements, Au–Bi2S3 can deposit higher radiation dose within tumors in the form of high energy electrons. On the other hand, Au–Bi2S3 can remarkably improve the utilization of a large number of X-ray-induced low energy electrons during radiotherapy for nonoxygen dependent free radicals generation even in hypoxic condition. This feature of Schottky-type heterostructures Au–Bi2S3 attributes to the generated Schottky barrier between metal Au and semiconductor Bi2S3, which can trap the X-ray-generated electrons and transfer them to Au, resulting in efficient separation of the electron–hole pairs. Then, because of the matched potential between the conduction band of Bi2S3 and overexpressed H2O2 within tumor, the Au–Bi2S3 HNSCs can decompose the intracellular H2O2 into highly toxic •OH for selective radiosensitization in tumor. As a consequence, this kind of nanoparticle provides an idea to develop rational designed Schottky-type heterostructures as efficient radiosensitizers for enhanced radiotherapy of cancer.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Tumour Microenvironment after Radiotherapy: Mechanisms of Resistance and Recurrence
Barker, H. E., Paget, J. T. E., Khan, A. A., & Harrington, K. J. (2015) · Nature Reviews Cancer · doi:10.1038/nrc3958 · Cited by 2,144
Cheng, Y., Cheng, H., Jiang, C., Qiu, X., Wang, K., Huan, W., Yuan, A., Wu, J., & Hu, Y. (2015) · Nature Communications · doi:10.1038/ncomms9785 · Cited by 941
Cited by
Shahbazi, M.-A., Faghfouri, L., Ferreira, M. P. A., Figueiredo, P., Maleki, H., Sefat, F., Hirvonen, J., & Santos, H. A. (2020) · Chemical Society Reviews · doi:10.1039/c9cs00283a · Cited by 523
X-ray-activated nanosystems for theranostic applications
Chen, X., Song, J., Chen, X., & Yang, H. (2019) · Chemical Society Reviews · doi:10.1039/c8cs00921j · Cited by 401
Reactive Oxygen Species‐Regulating Strategies Based on Nanomaterials for Disease Treatment
Zhang, C., Wang, X., Du, J., Gu, Z., & Zhao, Y. (2021) · Advanced Science · doi:10.1002/advs.202002797 · Cited by 401
Self-citationChong, Y., Liu, Q., & Ge, C. (2021) · Nano Today · doi:10.1016/j.nantod.2021.101076 · Cited by 339
Xiao, L., Chen, B., Wang, W., Tian, T., Qian, H., Li, X., & Yu, Y. (2023) · Advanced Science · doi:10.1002/advs.202302141 · Cited by 64
Metadata
- Authors
- Wang, X., Zhang, C., Du, J., Dong, X., Jian, S., Yan, L., Gu, Z., & Zhao, Y.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-04-10
- Volume
- 13
- Issue
- 5
- Pages
- 5947-5958
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2937682709
- Cited by
- 186
- References
- 2
- FWCI
- 15.98
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.