Rapid and sensitive detection of exosomal microRNAs by terahertz metamaterials

Exosomal microRNAs (miRNAs) are among the most common biomarkers for tumor diagnosis. However, single-miRNA detection lacks ideal sensitivity and specificity for diagnosing a certain tumor in clinics. In this work, we fabricated a convenient multi-miRNA detection platform for sensitive and specific detection on exosomal miRNAs in the plasma of patients using a terahertz (THz) metamaterial biosensor on the basis of strand displacement amplification (SDA) and AuNPs. The proposed multi-miRNA detection platform was highly sensitive to miRNA-15, miRNA-21, miRNA-145, miRNA-155, miRNA-423, and miRNA-451, and the limit of detection (LOD) obtained were 12.54 aM, 19.66 aM, 17.50 aM, 25.40 aM, 24.11 aM and 26.59 aM, respectively. The biosensor we constructed can be used to diagnose pancreatic cancer patients effectively in complex clinical samples. The use of multiple miRNAs demonstrated strong practicality in the combined diagnosis of patients with pancreatic cancer. These studies demonstrate that the multi-RNA detection platform boasts advantages such as low cost, rapid, high sensitivity, and specificity, offering a potential tool for future clinical applications.

Authors

Institutions

Publication Details

Journal
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy
Published
2025-01-16
DOI
https://doi.org/10.1016/j.saa.2025.125745
Citations
6
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
4.84
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rapid and sensitive detection of exosomal microRNAs by terahertz metamaterials

Jining Li, Yi Zhou, Zhen Zong, Ling Liang et al.
6 citations
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy
Advanced biosensing and bioanalysis techniques
4.84
article

Rapid and sensitive detection of exosomal microRNAs by terahertz metamaterials

Jining Li, Yi Zhou, Zhen Zong, Ling Liang, Ke Yang, Hao Huang, Fengxin Xie, Huiyan Tian, Mei Xin, Yü Liu, Yang Xiang, Weidong Jin
article en
6 citations

Abstract

Exosomal microRNAs (miRNAs) are among the most common biomarkers for tumor diagnosis. However, single-miRNA detection lacks ideal sensitivity and specificity for diagnosing a certain tumor in clinics. In this work, we fabricated a convenient multi-miRNA detection platform for sensitive and specific detection on exosomal miRNAs in the plasma of patients using a terahertz (THz) metamaterial biosensor on the basis of strand displacement amplification (SDA) and AuNPs. The proposed multi-miRNA detection platform was highly sensitive to miRNA-15, miRNA-21, miRNA-145, miRNA-155, miRNA-423, and miRNA-451, and the limit of detection (LOD) obtained were 12.54 aM, 19.66 aM, 17.50 aM, 25.40 aM, 24.11 aM and 26.59 aM, respectively. The biosensor we constructed can be used to diagnose pancreatic cancer patients effectively in complex clinical samples. The use of multiple miRNAs demonstrated strong practicality in the combined diagnosis of patients with pancreatic cancer. These studies demonstrate that the multi-RNA detection platform boasts advantages such as low cost, rapid, high sensitivity, and specificity, offering a potential tool for future clinical applications.

Spectrochimica Acta Part A Molecular and Biomolecular SpectroscopyVol. 330
Army Medical University (CN), Tianjin University (CN), Southwest Hospital (CN), First People's Hospital of Chongqing (CN), Southwest Jiaotong University (CN)
Openalex Percentile: Top 6%
Advanced biosensing and bioanalysis techniques
4.84
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.