Interfacial Self‐Assembly Ag‐Ag <sub>2</sub> S Asymmetric Ordered Nanowires for Photoelectrochemical Intelligent Detection of Dual LncRNAs
ABSTRACT The random stacking and intrinsic high symmetry of substrate materials seriously affect the photoelectrochemical (PEC) detection performance. Herein, taking silver nanowires as templates, the silver‐silver sulfide (Ag‐Ag 2 S) asymmetric ordered nanowires (AONs) are prepared by the interfacial self‐assembly and interface‐confined sulfurization strategies. Based on the anisotropic characteristics of Ag‐Ag 2 S AONs on two sides, a novel PEC platform is reported for dual long non‐coding RNAs (lncRNAs) co‐detection in plasma exosomes, with machine learning‐assisted data analysis for cancer intelligent diagnosis. The photocurrent response of Ag‐Ag 2 S AONs is 16 times that of disordered Ag‐Ag 2 S, while finite‐difference time‐domain and density functional theory simulations confirm the optical anisotropy of Ag‐Ag 2 S AONs. Employing magnetic separation to differentiate signals, this developed PEC biosensor achieves selective recognition for lncRNAs MALAT1 and HOTAIR with low detection limits of 1.5 and 1.7 fM, respectively. Importantly, machine learning‐assisted Ag‐Ag 2 S AONs in distinguishing lung cancer patients from healthy individuals can reach 90% accuracy. The study combined the integration of advanced sensing materials and machine learning model, providing a new approach for intelligent monitoring of biomarkers.
Authors
- Ruiying Yang (ORCID: https://orcid.org/0000-0002-5720-1271)
- Chengzhou Zhu (ORCID: https://orcid.org/0000-0003-0679-7965)
- Jiarui Wei
- Wenbo Liu (ORCID: https://orcid.org/0000-0002-4992-7785)
- Mengjiao Mei
- Sirong Li
- Wenchao Geng
- Shang Chen
- Zhiyi Yan
- Jiangying Ji
- Siyu Liu
Institutions
- Zhengzhou University (CN)
- Central China Normal University (CN)
- Henan University of Engineering (CN)
Publication Details
- Journal
- Small
- Published
- 2026-08-03
- DOI
- https://doi.org/10.1002/smll.74483
- Primary Topic
- Advanced biosensing and bioanalysis techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Henan Province