Label-Free Direct Detection of MiRNAs with Poly-Silicon Nanowire Biosensors

He, Jing; Zhu, Jianjun; Jiang, Bin; Zhao, Yulan

doi:10.1007/978-1-4939-6866-4_20

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…Their one-dimensional structure makes it easier to immobilize bio-recognition components and increases the efficiency of charge transfer, increasing the sensitivity of the biosensors ( Gao et al, 2013 ). A study ( He et al, 2017 ) explored the potential of silicon nanowire (SiNW) biosensors which are a promising tool for miRNA detection due to their rapid reaction times and heightened sensitivity. They present a well-established method involving poly-silicon nanowire biosensors for detecting miRNA (let-7b), achieving LOD of 1 fM (femtomolar) ( He et al, 2017 ) ( Table 1 ).…”

Section: Introductionmentioning

confidence: 99%

“…A study ( He et al, 2017 ) explored the potential of silicon nanowire (SiNW) biosensors which are a promising tool for miRNA detection due to their rapid reaction times and heightened sensitivity. They present a well-established method involving poly-silicon nanowire biosensors for detecting miRNA (let-7b), achieving LOD of 1 fM (femtomolar) ( He et al, 2017 ) ( Table 1 ). In another study, PAn-modified SiNW was used to detect miRNAs by means of a nano-gapped microelectrode-based biosensor.…”

Section: Introductionmentioning

confidence: 99%

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A concise overview of advancements in ultrasensitive biosensor development

Shahid,

Nazir,

Khan

et al. 2023

Front. Bioeng. Biotechnol.

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Electrochemical biosensing has evolved as a diverse and potent method for detecting and analyzing biological entities ranging from tiny molecules to large macromolecules. Electrochemical biosensors are a desirable option in a variety of industries, including healthcare, environmental monitoring, and food safety, due to significant advancements in sensitivity, selectivity, and portability brought about by the integration of electrochemical techniques with nanomaterials, bio-recognition components, and microfluidics. In this review, we discussed the realm of electrochemical sensors, investigating and contrasting the diverse strategies that have been harnessed to push the boundaries of the limit of detection and achieve miniaturization. Furthermore, we assessed distinct electrochemical sensing methods employed in detection such as potentiometers, amperometers, conductometers, colorimeters, transistors, and electrical impedance spectroscopy to gauge their performance in various contexts. This article offers a panoramic view of strategies aimed at augmenting the limit of detection (LOD) of electrochemical sensors. The role of nanomaterials in shaping the capabilities of these sensors is examined in detail, accompanied by insights into the chemical modifications that enhance their functionality. Furthermore, our work not only offers a comprehensive strategic framework but also delineates the advanced methodologies employed in the development of electrochemical biosensors. This equips researchers with the knowledge required to develop more accurate and efficient detection technologies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A concise overview of advancements in ultrasensitive biosensor development

Shahid,

Nazir,

Khan

et al. 2023

Front. Bioeng. Biotechnol.

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show abstract

“…Silicon nanowire sensors (SiNW) [1,2] (see Figure 1) are promising devices used to detect the presence or concentration of different biological species, such as cancer cells [3], DNA and miRNA molecules [4,5], and proteins [6]. The sensors are being developed for the early detection of cardiovascular diseases [7], prostate cancer [8], breast cancer [9], gastric cancer [10], flu [11], and uric acid in human blood [12].…”

Section: Introductionmentioning

confidence: 99%

Bayesian inversion for nanowire field-effect sensors

2019

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Nanowire field-effect sensors have recently been developed for label-free detection of biomolecules. In this work, we introduce a computational technique based on Bayesian estimation to determine the physical parameters of the sensor and, more importantly, the properties of the analyte molecules. To that end, we first propose a PDE based model to simulate the device charge transport and electrochemical behavior. Then, the adaptive Metropolis algorithm with delayed rejection (DRAM) is applied to estimate the posterior distribution of unknown parameters, namely molecule charge density, molecule density, doping concentration, and electron and hole mobilities. We determine the device and molecules properties simultaneously, and we also calculate the molecule density as the only parameter after having determined the device parameters. This approach makes it possible not only to determine unknown parameters, but it also shows how well each parameter can be determined by yielding the probability density function (pdf).

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