Biosensors Based on Mechanical and Electrical Detection Techniques.
Biosensors Based on Mechanical and Electrical Detection Techniques.
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DOI：
10.3390/s20195605
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发表时间：
2020-09-30
期刊：
影响因子：
--
通讯作者：
Kar-Narayan S
中科院分区：
文献类型：
--
作者：
Chalklen T;Jing Q;Kar-Narayan S
生物传感器是生物学和生物医学的强大分析工具，应用范围从药物发现到医学诊断、食品安全以及农业和环境监测。通常，生物识别受体（例如酶、抗体和核酸）固定在表面上，并用于与一种或多种特定分析物相互作用以产生物理或化学变化，该变化可以被传感器捕获并转换为光或电信号。然而，许多现有的生物传感方法依赖于化学、电化学和光学方法来识别和检测特定目标，并且通常是：复杂、昂贵、耗时、缺乏便携性，或者可能需要由合格人员进行集中测试。鉴于大多数光学和电化学技术普遍依赖于标记分子，本综述将重点关注机械和电气检测技术，这些技术可以提供广泛物种的信息，而无需标记。这些技术通常能够实时提供数据，具有良好的时间敏感性。本综述将涵盖机械和电气生物传感器的开发进展，强调其中的挑战和机遇。
Biosensors are powerful analytical tools for biology and biomedicine, with applications ranging from drug discovery to medical diagnostics, food safety, and agricultural and environmental monitoring. Typically, biological recognition receptors, such as enzymes, antibodies, and nucleic acids, are immobilized on a surface, and used to interact with one or more specific analytes to produce a physical or chemical change, which can be captured and converted to an optical or electrical signal by a transducer. However, many existing biosensing methods rely on chemical, electrochemical and optical methods of identification and detection of specific targets, and are often: complex, expensive, time consuming, suffer from a lack of portability, or may require centralised testing by qualified personnel. Given the general dependence of most optical and electrochemical techniques on labelling molecules, this review will instead focus on mechanical and electrical detection techniques that can provide information on a broad range of species without the requirement of labelling. These techniques are often able to provide data in real time, with good temporal sensitivity. This review will cover the advances in the development of mechanical and electrical biosensors, highlighting the challenges and opportunities therein.
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影响因子：
8.4
作者：
Bergveld, P
通讯作者：
Bergveld, P
影响因子：
8.4
作者：
Alodhayb, Abdullah;Rahman, S. M. Saydur;Beaulieu, L. Y.
通讯作者：
Beaulieu, L. Y.
DOI：
10.1073/pnas.0504917102
发表时间：
2005-10-11
影响因子：
11.1
作者：
Backmann, N;Zahnd, C;Gerber, C
通讯作者：
Gerber, C
影响因子：
12.6
作者：
Agarwal, Rahul;Sarkar, Arnab;Chakraborty, Suman
通讯作者：
Chakraborty, Suman
影响因子：
2.8
作者：
Bernardeschi, Irene;Greco, Francesco;Beccai, Lucia
通讯作者：
Beccai, Lucia