Yao Yiming, Zhao Kai, Jia Haoxin, Wei Zhengxing, Huo Yiyang, Zhang Yi, Zhang Kaihuan
Liaoning Key Laboratory of Marine Sensing and Intelligent Detection, Department of Information Science and Technology, Dalian Maritime University, Dalian 116026, China.
2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Biosensors (Basel). 2025 Aug 1;15(8):496. doi: 10.3390/bios15080496.
Since the initial use of biological ion channels to detect single-stranded genomic base pair differences, label-free and highly sensitive resistive pulse sensing (RPS) with nanopores has made remarkable progress in single-molecule analysis. By monitoring transient ionic current disruptions caused by molecules translocating through a nanopore, this technology offers detailed insights into the structure, charge, and dynamics of the analytes. In this work, the RPS platforms based on biological, solid-state, and other sensing pores, detailing their latest research progress and applications, are reviewed. Their core capability is the high-precision characterization of tiny particles, ions, and nucleotides, which are widely used in biomedicine, clinical diagnosis, and environmental monitoring. However, current RPS methods involve bottlenecks, including limited sensitivity (weak signals from sub-nanometer targets with low SNR), complex sample interference (high false positives from ionic strength, etc.), and field consistency (solid-state channel drift, short-lived bio-pores failing POCT needs). To overcome this, bio-solid-state fusion channels, in-well reactors, deep learning models, and transfer learning provide various options. Evolving into an intelligent sensing ecosystem, RPS is expected to become a universal platform linking basic research, precision medicine, and on-site rapid detection.
自从最初使用生物离子通道来检测单链基因组碱基对差异以来，基于纳米孔的无标记且高灵敏度的电阻脉冲传感（RPS）在单分子分析方面取得了显著进展。通过监测分子穿过纳米孔时引起的瞬态离子电流中断，该技术能够深入了解分析物的结构、电荷和动力学。在这项工作中，我们综述了基于生物、固态和其他传感孔的RPS平台，详细介绍了它们的最新研究进展和应用。它们的核心能力是对微小颗粒、离子和核苷酸进行高精度表征，广泛应用于生物医学、临床诊断和环境监测。然而，当前的RPS方法存在瓶颈，包括灵敏度有限（来自亚纳米目标的弱信号，信噪比低）、复杂的样品干扰（离子强度等导致的高假阳性）以及场一致性（固态通道漂移、寿命短的生物孔无法满足即时检测需求）。为了克服这些问题，生物 - 固态融合通道、孔内反应器、深度学习模型和迁移学习提供了多种选择。RPS正朝着智能传感生态系统发展，有望成为连接基础研究、精准医学和现场快速检测的通用平台。
