Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 174

The DOI matches its Crossref record.

Noninvasive Staging of Kidney Dysfunction Enabled by Renal‐Clearable Luminescent Gold Nanoparticles

Open access
Yu, Mengxiao, Zhou, Jiancheng, Du, Bujie, Ning, Xuhui, Authement, Craig, Gandee, Leah, Kapur, Payal, Hsieh, Jer‐Tsong, Zheng, Jie·2016·Angewandte Chemie International Edition

Abstract

As a “silent killer”, kidney disease is often hardly detected at an early stage but can cause lethal kidney failure later on. Thus, a preclinical imaging technique that can readily differentiate between the stages of kidney dysfunction is highly desired for improving our fundamental understanding of kidney disease progression. Herein, we report that in vivo fluorescence imaging, enabled by renal‐clearable near‐infrared‐emitting gold nanoparticles, can noninvasively detect kidney dysfunction, report on the dysfunctional stages, and even reveal adaptive function in a mouse model of unilateral obstructive nephropathy, which cannot be diagnosed with routine kidney function markers. These results demonstrate that low‐cost fluorescence kidney functional imaging is highly sensitive and useful for the longitudinal, noninvasive monitoring of kidney dysfunction progression in preclinical research.

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 · 10.1002/anie.201511148

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 174

Metadata

Authors
Yu, M., Zhou, J., Du, B., Ning, X., Authement, C., Gandee, L., Kapur, P., Hsieh, J., & Zheng, J.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2016-01-22
Volume
55
Issue
8
Pages
2787-2791
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2291540813
Cited by
174
References
0
FWCI
15.24
Type
journal article
Language
en
Open access
green

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: Noninvasive Staging of Kidney Dysfunction Enabled by Renal‐Clearable Luminescent Gold Nanoparticles. https://app.cochat.ai/papers/10.1002/anie.201511148
The paper
Yu, M., Zhou, J., Du, B., Ning, X., Authement, C., Gandee, L., Kapur, P., Hsieh, J., & Zheng, J. (2016). Noninvasive Staging of Kidney Dysfunction Enabled by Renal‐Clearable Luminescent Gold Nanoparticles. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201511148

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.