The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Recent progress in biomedical applications of persistent luminescence nanoparticles
Abstract
Persistent luminescence nanoparticles (PLNPs) are an emerging group of promising luminescent materials that can remain luminescent after the excitation ceases. In the past decade, PLNPs with intriguing optical properties have been developed and their applications in biomedicine have been widely studied. Due to the ultra-long decay time of persistent luminescence, autofluorescence interference in biosensing and bioimaging can be efficiently eliminated. Moreover, PLNPs can remain luminescent for hours, making them valuable in bio-tracing. Also, persistent luminescence imaging can guide cancer therapy with a high signal-to-noise ratio (SNR) and superior sensitivity. Briefly, PLNPs are demonstrated to be a newly-emerging class of functional materials with unprecedented advantages in biomedicine. In this review, we summarized recent advances in the preparation of PLNPs and the applications of PLNPs in biosensing, bioimaging and cancer therapy.
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
Second window for in vivo imaging
Smith, A. M., Mancini, M. C., & Nie, S. (2009) · Nature Nanotechnology · doi:10.1038/nnano.2009.326 · Cited by 2,848
Cited by
Molecular Probes for Autofluorescence-Free Optical Imaging
Jiang, Y., & Pu, K. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00506 · Cited by 426
Sun, S.-K., Wang, H.-F., & Yan, X.-P. (2018) · Accounts of Chemical Research · doi:10.1021/acs.accounts.7b00619 · Cited by 384
Tan, H., Wang, T., Shao, Y., Yu, C., & Hu, L. (2019) · Frontiers in Chemistry · doi:10.3389/fchem.2019.00387 · Cited by 59
Metadata
- Authors
- Wang, J., Ma, Q., Wang, Y., Shen, H., & Yuan, Q.
- Venue
- Nanoscale
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2017
- Volume
- 9
- Issue
- 19
- Pages
- 6204-6218
- ISSN
- 2040-3364 (ISSN-L)
- 2040-3372
- OpenAlex
- W2606790836
- Cited by
- 200
- References
- 1
- FWCI
- 9.71
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Recent progress in biomedical applications of persistent luminescence nanoparticles. https://app.cochat.ai/papers/10.1039/c7nr01488k
- The paper
- Wang, J., Ma, Q., Wang, Y., Shen, H., & Yuan, Q. (2017). Recent progress in biomedical applications of persistent luminescence nanoparticles. Nanoscale. https://doi.org/10.1039/c7nr01488k
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.