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Nanostructured Interface-Engineered Field-Effect Transistor Biosensors for Sensitive Detection of Serum Mirnas

The Innovation Materials(2024)

Cited 1|Views13
Abstract
The efficient detection of disease-relevant biomolecules in untreated clinical samples is highly desired, especially for acute diseases. Field-effect transistor (FET) biosensors allow label-free and rapid detection of biomolecules through the measurement of their intrinsic charges. However, the sensitivity of FET biosensors would be undermined by the charge screening effect in practical biological media with high ionic strength. Here, we report the design and performance of a nanostructured interface-engineered field effect transistor (NIE FET) biosensor for highly sensitive detection of cardiovascular disease (CVD)-associated miRNAs in serum samples. Molecular dynamic simulations and electrochemical characterizations demonstrate that the nanostructured interface with concave regions alleviates the charge screening effect and enlarges the Debye length. The rationally designed NIE FET biosensor exhibits high sensitivity and reproducibility in detecting miRNA in untreated serum samples with a detection limit of pM level. Benefiting from its excellent detection capabilities, NIE FET reveals the relationship between miRNAs and CVDs and realizes the effective classification of different CVD types with the help of machine learning algorithms. The construction of NIE FET defines a robust strategy for electrical biomolecular detection in practical clinical samples.
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要点】:本文报道了一种纳米结构界面优化的场效应晶体管(NIE FET)生物传感器,用于高灵敏度检测血清中与心血管疾病相关的微小RNA(miRNAs),并通过机器学习算法实现不同类型CVD的有效分类。

方法】:通过分子动力学模拟和电化学表征,研究了纳米结构界面如何减轻电荷屏蔽效应并增大德拜长度,提高了NIE FET生物传感器的灵敏度。

实验】:实验采用未经处理的血清样本,NIE FET生物传感器在检测miRNA时展现出高灵敏度和重复性,检测限达到皮摩尔(pM)级别。使用该传感器成功揭示了miRNAs与CVD之间的关系,并通过机器学习算法实现了对不同CVD类型的有效分类。