The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Engineering Persistent Luminescence Nanoparticles for Biological Applications: From Biosensing/Bioimaging to Theranostics
Abstract
Persistent luminescence nanoparticles (PLNPs) are unique optical materials emitting long-lasting luminescence after ceasing excitation. Such a unique optical feature allows luminescence detection without constant external illumination to avoid the interferences of autofluorescence and scattering light from biological fluids and tissues. Besides, near-infrared (NIR) PLNPs have advantages of deep penetration and the reactivation of the persistent luminescence (PL) by red or NIR light. These features make the application of NIR-emitting PLNPs in long-term bioimaging no longer limited by the lifetime of PL. To take full advantage of PLNPs for biological applications, the versatile strategies for bridging PLNPs and biological system become increasingly significant for the design of PLNPs-based nanoprobes. In this Account, we summarize our systematic achievements in the biological applications of PLNPs from biosensing/bioimaging to theranostics with emphasizing the engineering strategies for fabricating specific PLNPs-based nanoprobes. We take surface engineering and manipulating energy transfer as the major principles to design various PLNPs-based nanoprobes based on the nature of interactions between nanoprobes and targets. We have developed target-induced formation or interruption of fluorescence resonance energy transfer systems for autofluorescence-free biosensing and imaging of cancer biomarkers. We have decorated single or dual targeting ligands on PLNPs for tumor-targeted imaging, and integrated other modal imaging agents into PLNPs for multimodal imaging. We have also employed specific functionalization for various biomedical applications including chemotherapy, photodynamic therapy, photothermal therapy, stem cells tracking and PL imaging-guided gene therapy. Besides, we have modified PLNPs with multiple functional units to achieve challenging metastatic tumor theranostics. The proposed design principle and comprehensive strategies show great potential in guiding the design of PLNPs nanoprobes and promoting further development of PLNPs in the fields of biological science and medicine. We conclude this Account by outlining the future directions to further promote the practical application of PLNPs. The novel protocols for the synthesis of small-size, monodisperse, and water-soluble PLNPs with high NIR PL intensity and superlong afterglow are the vibrant directions for the biomedical applications of PLNPs. In-depth theories and evidence on luminescence mechanism of PLNPs are highly desired for further improvement of their luminescence performance. Furthermore, other irradiations without tissue penetrating depth limit, such as X-ray, are encouraged for use in energy storage and re-excitation of PLNPs, enabling imaging in deep tissue in vivo and integrating other X-ray sensitized theranostic techniques such as computed tomography imaging and radiotherapy. Last but not least, PLNPs-based nanoprobes and the brand new hybrids of PLNPs with other nanomaterials show a bright prospect for accurate diagnosis and efficient treatment of diseases besides tumors.
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
Functional Nanomaterials for Phototherapies of Cancer
Cheng, L., Wang, C., Feng, L., Yang, K., & Liu, Z. (2014) · Chemical Reviews · doi:10.1021/cr400532z · Cited by 2,425
Nanochemistry and Nanomedicine for Nanoparticle-based Diagnostics and Therapy
Chen, G., Roy, I., Yang, C., & Prasad, P. N. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00148 · Cited by 1,499
Pan, Z., Lu, Y.-Y., & Liu, F. (2012) · Nature Materials · doi:10.1038/nmat3173 · Cited by 1,415
Long persistent phosphors—from fundamentals to applications
Li, Y., Gecevicius, M., & Qiu, J. (2016) · Chemical Society Reviews · doi:10.1039/c5cs00582e · Cited by 1,368
Maldiney, T., Bessière, A., Seguin, J., Teston, E., Sharma, S. K., Viana, B., Bos, A. J. J., Dorenbos, P., Bessodes, M., Gourier, D., et al. (2014) · Nature Materials · doi:10.1038/nmat3908 · Cited by 1,096
Multimodality Imaging Probes: Design and Challenges
Louie, A. (2010) · Chemical Reviews · doi:10.1021/cr9003538 · Cited by 1,044
Advanced materials and processing for drug delivery: The past and the future
Zhang, Y., Chan, H. F., & Leong, K. W. (2013) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2012.10.003 · Cited by 1,000
Nanoprobes with near-infrared persistent luminescence for in vivo imaging
le Masne de Chermont, Q., Chanéac, C., Seguin, J., Pellé, F., Maîtrejean, S., Jolivet, J.-P., Gourier, D., Bessodes, M., & Scherman, D. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0702427104 · Cited by 834
Abdukayum, A., Chen, J.-T., Zhao, Q., & Yan, X.-P. (2013) · Journal of the American Chemical Society · doi:10.1021/ja404243v · Cited by 712
Self-citationLi, Z., Zhang, Y., Wu, X., Huang, L., Li, D., Fan, W., & Han, G. (2015) · Journal of the American Chemical Society · doi:10.1021/jacs.5b00872 · Cited by 443
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
Geng, X., Gao, D., Hu, D., Liu, Q., Liu, C., Yuan, Z., Zhang, X., Liu, X., Sheng, Z., Wang, X., et al. (2020) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.0c16872 · Cited by 61
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
- Sun, S.-K., Wang, H.-F., & Yan, X.-P.
- Venue
- Accounts of Chemical Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-04-17
- Volume
- 51
- Issue
- 5
- Pages
- 1131-1143
- ISSN
- 0001-4842 (ISSN-L)
- 1520-4898
- OpenAlex
- W2801124226
- Cited by
- 384
- References
- 37
- FWCI
- 15.45
- 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: Engineering Persistent Luminescence Nanoparticles for Biological Applications: From Biosensing/Bioimaging to Theranostics. https://app.cochat.ai/papers/10.1021/acs.accounts.7b00619
- The paper
- Sun, S.-K., Wang, H.-F., & Yan, X.-P. (2018). Engineering Persistent Luminescence Nanoparticles for Biological Applications: From Biosensing/Bioimaging to Theranostics. Accounts of Chemical Research. https://doi.org/10.1021/acs.accounts.7b00619
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.