Cited by 445Luminescence and Fluorescent MaterialsNanoplatforms for cancer theranosticsMolecular Sensors and Ion Detection

Bright Aggregation‐Induced‐Emission Dots for Targeted Synergetic NIR‐II Fluorescence and NIR‐I Photoacoustic Imaging of Orthotopic Brain Tumors

Sheng, Zonghai, Guo, Bing, Hu, Dehong, Xu, Shidang, Wu, Wenbo, Liew, Weng Heng, Yao, Kui, Jiang, Jingying +3 more·2018·Advanced Materials

Abstract

Precise diagnostics are of significant importance to the optimal treatment outcomes of patients bearing brain tumors. NIR‐II fluorescence imaging holds great promise for brain‐tumor diagnostics with deep penetration and high sensitivity. This requires the development of organic NIR‐II fluorescent agents with high quantum yield (QY), which is difficult to achieve. Herein, the design and synthesis of a new NIR‐II fluorescent molecule with aggregation‐induced‐emission (AIE) characteristics is reported for orthotopic brain‐tumor imaging. Encapsulation of the molecule in a polymer matrix yields AIE dots showing a very high QY of 6.2% with a large absorptivity of 10.2 L g −1 cm −1 at 740 nm and an emission maximum near 1000 nm. Further decoration of the AIE dots with c‐RGD yields targeted AIE dots, which afford specific and selective tumor uptake, with a high signal/background ratio of 4.4 and resolution up to 38 µm. The large NIR absorptivity of the AIE dots facilitates NIR‐I photoacoustic imaging with intrinsically deeper penetration than NIR‐II fluorescence imaging and, more importantly, precise tumor‐depth detection through intact scalp and skull. This research demonstrates the promise of NIR‐II AIE molecules and their dots in dual NIR‐II fluorescence and NIR‐I photoacoustic imaging for precise brain cancer diagnostics.

Integrity signals

Registry

Crossref · 10.1002/adma.201800766

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

The citation lists haven’t been fetched yet

References 44 · Cited by 445

Authors
Sheng, Z., Guo, B., Hu, D., Xu, S., Wu, W., Liew, W. H., Yao, K., Jiang, J., Liu, C., Zheng, H., & Liu, B.
Affiliations
  • Chinese Academy of Sciences (CN)
  • National University of Singapore (SG)
  • Institute of Materials Research and Engineering (SG)
Corresponding author
  • Zheng, Hairong
  • Liu, Bin
Venue
Advanced Materials
Publisher
Wiley
Published
2018-05-28
Volume
30
Issue
29
Pages
e1800766-e1800766
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2805542742
Cited by
445
References
44
Citations by year
2026: 21 · 2025: 32 · 2024: 38 · 2023: 54 · 2022: 61 · 2021: 85 · 2020: 76 · 2019: 69 · 2018: 9
FWCI
22.31
Type
journal article
Language
en
Open access
closed
Locations
  • Advanced Materials (publishedVersion)
  • PubMed (publishedVersion)
  • National University of Singapore (submittedVersion)
Funders
  • National Research Foundation Singapore (R279‐000‐483‐281, R279‐000‐444‐281)
  • National University of Singapore (R279‐000‐482‐133)
  • National Natural Science Foundation of China (81571745, 81401521, 81327801, 81771906)
Topics
  • Physical Sciences › Materials Science › Materials Chemistry › Luminescence and Fluorescent Materials
  • Physical Sciences › Engineering › Biomedical Engineering › Nanoplatforms for cancer theranostics
  • Physical Sciences › Chemistry › Spectroscopy › Molecular Sensors and Ion Detection
Keywords
aggregation-induced emission, NIR-II fluorescence, brain tumors, polymer encapsulation, quantum yield, dual-modality imaging

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