Urease-Driven Janus Nanomotors for Dynamic Enrichment and Multiplexed Detection of Bladder Cancer MicroRNAs in Urine

Bladder cancer diagnosis typically involves approaches such as cystoscopy, biopsy, urine cytology, and medical imaging. However, these invasive procedures carry a risk of complications, and direct in vitro detection on clinical samples often results in low sensitivity. Therefore, this study proposed urease-driven magnetic nanomotors for the simultaneous detection of bladder cancer biomarkers miRNA-21 and miRNA-182 in urine samples, aiming for noninvasive diagnosis. The nanomotor was constructed from gold nanorods, mesoporous organo-silica, Fe<sub>3</sub>O<sub>4</sub>, and hairpin DNA (hDNA), functioning as a recognition probe for the target miRNAs. In the urea solution, urease catalyzed urea into ammonia and carbon dioxide, propelling the nanomotor for about 60 min, which enhanced the capacity of the probes to capture the target miRNAs. Subsequently, magnetic enrichment enabled highly sensitive dual-miRNA analysis, allowing quantification of miRNA-21 and miRNA-182 with detection limits of 29 and 362 fM, respectively. The nanoprobes also effectively detected miRNAs in spiked urine samples. This simultaneous detection of multiple miRNAs increased the reliability of cancer diagnosis, presenting a novel noninvasive strategy for bladder cancer detection through precise in vitro analysis of actual urine samples.

Authors

Institutions

Publication Details

Journal
ACS Sensors
Published
2025-02-05
DOI
https://doi.org/10.1021/acssensors.4c02996
Citations
11
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
13.84

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Urease-Driven Janus Nanomotors for Dynamic Enrichment and Multiplexed Detection of Bladder Cancer MicroRNAs in Urine

Hong Zhou, Shaohui Zheng, Minghui Chen, Yiyang Xie et al.
11 citations
ACS Sensors
Micro and Nano Robotics
13.84
article

Urease-Driven Janus Nanomotors for Dynamic Enrichment and Multiplexed Detection of Bladder Cancer MicroRNAs in Urine

Hong Zhou, Shaohui Zheng, Minghui Chen, Yiyang Xie, Hong Wang, Xinran Zhang, Wenbei Xu, Canran Jiang, Qi Liu, Fang Zhou, Peipei Dou
article en
11 citations

Abstract

Bladder cancer diagnosis typically involves approaches such as cystoscopy, biopsy, urine cytology, and medical imaging. However, these invasive procedures carry a risk of complications, and direct in vitro detection on clinical samples often results in low sensitivity. Therefore, this study proposed urease-driven magnetic nanomotors for the simultaneous detection of bladder cancer biomarkers miRNA-21 and miRNA-182 in urine samples, aiming for noninvasive diagnosis. The nanomotor was constructed from gold nanorods, mesoporous organo-silica, Fe<sub>3</sub>O<sub>4</sub>, and hairpin DNA (hDNA), functioning as a recognition probe for the target miRNAs. In the urea solution, urease catalyzed urea into ammonia and carbon dioxide, propelling the nanomotor for about 60 min, which enhanced the capacity of the probes to capture the target miRNAs. Subsequently, magnetic enrichment enabled highly sensitive dual-miRNA analysis, allowing quantification of miRNA-21 and miRNA-182 with detection limits of 29 and 362 fM, respectively. The nanoprobes also effectively detected miRNAs in spiked urine samples. This simultaneous detection of multiple miRNAs increased the reliability of cancer diagnosis, presenting a novel noninvasive strategy for bladder cancer detection through precise in vitro analysis of actual urine samples.

ACS SensorsVol. 10(2)
Xuzhou Medical College (CN), China University of Mining and Technology (CN), Affiliated Hospital of Xuzhou Medical College (CN), Lanzhou University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province, Xuzhou Medical University, “333 Project” of Jiangsu Province, Fundamental Research Funds for the Central Universities
Zero hunger
Openalex Percentile: Top 1%
Micro and Nano Robotics
13.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.