Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 172

The DOI matches its Crossref record.

Self-Illuminating 64Cu-Doped CdSe/ZnS Nanocrystals for in Vivo Tumor Imaging

Open access
Sun, Xiaolian, Huang, Xinglu, Guo, Jinxia, Zhu, Wenlei, Ding, Yong, Niu, Gang, Wang, Andrew, Kiesewetter, Dale O., Wang, Zhong Lin, Sun, Shouheng, Chen, Xiaoyuan·2014·Journal of the American Chemical Society

Abstract

Construction of self-illuminating semiconducting nanocrystals, also called quantum dots (QDs), has attracted much attention recently due to their potential as highly sensitive optical probes for biological imaging applications. Here we prepared a self-illuminating QD system by doping positron-emitting radionuclide (64)Cu into CdSe/ZnS core/shell QDs via a cation-exchange reaction. The (64)Cu-doped CdSe/ZnS QDs exhibit efficient Cerenkov resonance energy transfer (CRET). The signal of (64)Cu can accurately reflect the biodistribution of the QDs during circulation with no dissociation of (64)Cu from the nanoparticles. We also explored this system for in vivo tumor imaging. This nanoprobe showed high tumor-targeting ability in a U87MG glioblastoma xenograft model (12.7% ID/g at 17 h time point) and feasibility for in vivo luminescence imaging of tumor in the absence of excitation light. The availability of these self-illuminating integrated QDs provides an accurate and convenient tool for in vivo tumor imaging and detection.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/ja410438n

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cited by

See all 172

Metadata

Authors
Sun, X., Huang, X., Guo, J., Zhu, W., Ding, Y., Niu, G., Wang, A., Kiesewetter, D. O., Wang, Z. L., Sun, S., & Chen, X.
Venue
Journal of the American Chemical Society
Published
2014-01-17
Volume
136
Issue
5
Pages
1706-1709
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2223071637
Cited by
172
References
0
FWCI
9.83
Type
journal article
Language
en
Open access
hybrid

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: Self-Illuminating 64Cu-Doped CdSe/ZnS Nanocrystals for in Vivo Tumor Imaging. https://app.cochat.ai/papers/10.1021/ja410438n
The paper
Sun, X., Huang, X., Guo, J., Zhu, W., Ding, Y., Niu, G., Wang, A., Kiesewetter, D. O., Wang, Z. L., Sun, S., & Chen, X. (2014). Self-Illuminating 64Cu-Doped CdSe/ZnS Nanocrystals for in Vivo Tumor Imaging. Journal of the American Chemical Society. https://doi.org/10.1021/ja410438n

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.