The DOI matches its Crossref record; 119 of the 119 references it cites were found in a registry or an index.
In vivo NIR-II fluorescence imaging for biology and medicine
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In the citing paper
“Near-infrared II (NIR-II) fluorophores possess transformative potential for biomedical applications, owing to their deep-tissue penetration, reduced tissue autofluorescence, and low phototoxicity.”
From Organic small-molecule NIR-II fluorophores for tumor phototheranostics (2026) · cites this paper as [39]
In the citing paper
“This fundamental property suppresses background noise, minimizes tissue autofluorescence, and results in negligible phototoxicity39,40.”
From Organic small-molecule NIR-II fluorophores for tumor phototheranostics (2026) · cites this paper as [39]
In the citing paper
“Notably, the NIR-II window can be further divided into the NIR-IIa (1300–1400 nm), NIR-IIb (1500–1700 nm) sub-windows, with the latter typically offering even more advantageous imaging performance39.”
From Organic small-molecule NIR-II fluorophores for tumor phototheranostics (2026) · cites this paper as [39]
Citations
Cites
A clearer vision for in vivo imaging
Weissleder, R. (2001) · Nature Biotechnology · doi:10.1038/86684 · Cited by 3,839
Near-infrared fluorophores for biomedical imaging
Hong, G., Antaris, A. L., & Dai, H. (2017) · Nature Biomedical Engineering · doi:10.1038/s41551-016-0010 · Cited by 3,048
Self-citationSecond 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
Noncovalent sidewall functionalization of single-walled carbon nanotubes for protein immobilization
Chen, R. J., Zhang, Y., Wang, D., & Dai, H. (2001) · Journal of the American Chemical Society · doi:10.1021/ja010172b · Cited by 2,534
Self-citationOptical Sectioning Deep Inside Live Embryos by Selective Plane Illumination Microscopy
Huisken, J., Swoger, J., Bene, F. D., Wittbrodt, J., & Stelzer, E. H. K. (2004) · Science · doi:10.1126/science.1100035 · Cited by 2,370
Gustafsson, M. G. L. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0406877102 · Cited by 2,270
A small-molecule dye for NIR-II imaging
Antaris, A. L., Chen, H., Cheng, K., Sun, Y., Hong, G., Qu, C., Diao, S., Deng, Z., Hu, X., Zhang, B., et al. (2016) · Nature Materials · doi:10.1038/nmat4476 · Cited by 1,778
Self-citationCarbon nanotubes in biology and medicine: In vitro and in vivo detection, imaging and drug delivery
Liu, Z., Tabakman, S. M., Welsher, K., & Dai, H. (2009) · Nano Research · doi:10.1007/s12274-009-9009-8 · Cited by 1,729
Self-citationIn vivo three-photon microscopy of subcortical structures within an intact mouse brain
Horton, N. G., Wang, K., Kobat, D., Clark, C. G., Wise, F. W., Schaffer, C. B., & Xu, C. (2013) · Nature Photonics · doi:10.1038/nphoton.2012.336 · Cited by 1,505
A route to brightly fluorescent carbon nanotubes for near-infrared imaging in mice
Welsher, K., Liu, Z., Sherlock, S. P., Robinson, J. T., Chen, Z., Daranciang, D., & Dai, H. (2009) · Nature Nanotechnology · doi:10.1038/nnano.2009.294 · Cited by 1,287
Self-citation
Cited by
Sorted by citations
NIR-II light in clinical oncology: opportunities and challenges
Zhang, Z., Du, Y., Shi, X., Wang, K., Qu, Q., Liang, Q. Y., Ma, X., He, K., Chi, C., Tang, J., et al. (2024) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-024-00892-0 · Cited by 397
Near-infrared II fluorescence imaging
Schmidt, E. L., Ou, Z., Ximendes, E. C., Cui, H., Keck, C. H. C., Jaque, D., & Hong, G. (2024) · Nature Reviews Methods Primers · doi:10.1038/s43586-024-00301-x · Cited by 392
High-brightness transition metal-sensitized lanthanide near-infrared luminescent nanoparticles
Ming, J., Chen, Y., Miao, H., Fan, Y., Wang, S., Chen, Z., Guo, Z., Guo, Z., Qi, L., Wang, X., et al. (2024) · Nature Photonics · doi:10.1038/s41566-024-01517-9 · Cited by 149
Organic photosensitizers: from molecular design to phototheranostics
Zhang, T., Qu, X., Shao, J., & Dong, X. (2025) · Chemical Society Reviews · doi:10.1039/d5cs00599j · Cited by 149
Molecular Gold Nanoclusters for Advanced NIR-II Bioimaging and Therapy
Baghdasaryan, A., & Dai, H. (2025) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00835 · Cited by 131
Self-citation
Metadata
- Authors
- Wang, F., Zhong, Y., Bruns, O., Liang, Y., & Dai, H.
- Affiliations
- University of Hong Kong (HK)
- Chinese Academy of Sciences (CN)
- Southern University of Science and Technology (CN)
- Corresponding author
- Dai, Hongjie
- Venue
- Nature Photonics
- Published
- 2024-03-04
- Volume
- 18
- Issue
- 6
- Pages
- 535-547
- ISSN
- 1749-4885 (ISSN-L)
- 1749-4893
- OpenAlex
- W4392376294
- Cited by
- 564
- References
- 119
- Citations by year
- 2026: 227 · 2025: 267 · 2024: 70
- FWCI
- 143.68
- Type
- journal article
- Language
- en
- Update notices
- correction (2024-05-28)
- Open access
- green
- hub.hku.hk
- Licence
- Locations
- Nature Photonics (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion, cc-by-nc-nd)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | Center for Scientific Review (DP1-NS-105737)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Physical Sciences › Chemistry › Spectroscopy › Molecular Sensors and Ion Detection
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Keywords
- NIR-II fluorescence imaging, fluorophore design, fluorescent probes, molecular imaging, single-cell imaging, wide-field imaging, fluorescence microscopy, small animal imaging, clinical translation, tissue autofluorescence, light scattering
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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.
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