Improving the reproducibility, accuracy, and stability of an electrochemical biosensor platform for point-of-care use

Chen, Lung-Chieh; Wang, Erick; Tai, Chun-San; Chiu, Yuan-Chen; Li, Chengwei; Lin, Yan Ren; Lee, Tsung‐Han; Huang, Ching‐Wen; Chen, Jung-Chih; Chen, Wen Liang

doi:10.1016/j.bios.2020.112111

Cited by 93 publications

(46 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These biosensors vary from each other based on the use of biorecognition components (BRC) and EAT for the detection process [1,4]. Typically, ECBs comprise three electrodes (working electrode (WE), reference electrode (RE), and counter electrode (CE)) that are placed in contact with the analyte solution in an electrochemical cell [1,6,53]. These three electrodes are connected with an electrochemical workstation that is capable of applying potential and measuring the electrochemical changes due to electron transfer at the interfacial region between the WE (transducer) and solution [46,51].…”

Section: Electrochemical Biosensorsmentioning

confidence: 99%

Section: Advances In Poct Devices: Prospects and Challenges In The CLmentioning

confidence: 99%

“…POCT provides health experts and patients with the opportunity to monitor health conditions and diagnose a disease quickly and accurately. Furthermore, the introduction of personalized heath care would be possible with the large-scale implementation of POCT [6,8,12]. This would allow for early-stage detection of cancer biomarkers, senescent β-cells in type-I diabetes patients, or beta-amyloids in Alzheimer's disease patients [65,297,298].…”

Section: Advances In Poct Devices: Prospects and Challenges In The CLmentioning

confidence: 99%

“…In the case of electrochemical biosensors (ECBs), the transducer converts the chemical signal to an electrical signal that allows for qualitative and quantitative identification of the target biomolecules [1,[3][4][5]. With the increasing risk of cancer, diabetes, viral infections, and other pathogenic diseases, point-of-care testing (POCT) systems have become essential in the health sector [4,[6][7][8]. As a result, research in ECBs has seen an exponential growth because they are inexpensive, provide fast and accurate responses, require almost no sample preparation, and are easy to use [3,[8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Metal Nanoparticles for Electrochemical Sensing: Progress and Challenges in the Clinical Transition of Point-of-Care Testing

et al. 2020

View full text Add to dashboard Cite

With the rise in public health awareness, research on point-of-care testing (POCT) has significantly advanced. Electrochemical biosensors (ECBs) are one of the most promising candidates for the future of POCT due to their quick and accurate response, ease of operation, and cost effectiveness. This review focuses on the use of metal nanoparticles (MNPs) for fabricating ECBs that has a potential to be used for POCT. The field has expanded remarkably from its initial enzymatic and immunosensor-based setups. This review provides a concise categorization of the ECBs to allow for a better understanding of the development process. The influence of structural aspects of MNPs in biocompatibility and effective sensor design has been explored. The advances in MNP-based ECBs for the detection of some of the most prominent cancer biomarkers (carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), Herceptin-2 (HER2), etc.) and small biomolecules (glucose, dopamine, hydrogen peroxide, etc.) have been discussed in detail. Additionally, the novel coronavirus (2019-nCoV) ECBs have been briefly discussed. Beyond that, the limitations and challenges that ECBs face in clinical applications are examined and possible pathways for overcoming these limitations are discussed.

show abstract

Section: Electrochemical Biosensorsmentioning

confidence: 99%

Section: Advances In Poct Devices: Prospects and Challenges In The CLmentioning

confidence: 99%

Section: Advances In Poct Devices: Prospects and Challenges In The CLmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Metal Nanoparticles for Electrochemical Sensing: Progress and Challenges in the Clinical Transition of Point-of-Care Testing

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In recent years, the development of electrochemical biosensors for DNA biomarkers has been of increasing interest to researchers due to their fast-analytical time, low cost and ease of miniaturization compared with traditional detection methods [ 9 , 10 , 11 , 12 , 13 , 14 ]. However, as the capture probe for electrochemical DNA sensor, single-stranded DNA is not rigid and lacks the ability to modulate the density of probes.…”

Section: Introductionmentioning

confidence: 99%

Electrochemical DNA Sensor for Sensitive BRCA1 Detection Based on DNA Tetrahedral-Structured Probe and Poly-Adenine Mediated Gold Nanoparticles

Feng

et al. 2020

Biosensors

View full text Add to dashboard Cite

BRCA1 is the biomarker for the early diagnosis of breast cancer. Detection of BRCA1 has great significance for the genetic analysis, early diagnosis and clinical treatment of breast cancer. In this work, we developed a simple electrochemical DNA sensor based on a DNA tetrahedral-structured probe (TSP) and poly-adenine (polyA) mediated gold nanoparticles (AuNPs) for the sensitive detection of BRCA1. A thiol-modified TSP was used as the scaffold on the surface of the screen-printed AuNPs electrode. The capture DNA (TSP) and reporter DNA were hybridized to the target DNA (BRCA1), respectively, to form the typical sandwich system. The nanocomposites of reporter DNA (polyA at the 5′ end) combined with AuNPs were employed for signal amplification which can capture multiple enzymes by the specificity between biotin and streptavidin. Measurements were completed in the electrochemical workstation by cyclic voltammetry and amperometry and we obtained the low limit of detection of 0.1 fM with the linear range from 1 fM to 1 nM. High sensitivity and good specificity of the proposed electrochemical DNA sensor showed potential applications in clinical early diagnosis for breast cancer.

show abstract

Machine Learning‐Reinforced Noninvasive Biosensors for Healthcare

Zhang

Wang

Liu

et al. 2021

Adv Healthcare Materials

View full text Add to dashboard Cite

The emergence and development of noninvasive biosensors largely facilitate the collection of physiological signals and the processing of health‐related data. The utilization of appropriate machine learning algorithms improves the accuracy and efficiency of biosensors. Machine learning‐reinforced biosensors are started to use in clinical practice, health monitoring, and food safety, bringing a digital revolution in healthcare. Herein, the recent advances in machine learning‐reinforced noninvasive biosensors applied in healthcare are summarized. First, different types of noninvasive biosensors and physiological signals collected are categorized and summarized. Then machine learning algorithms adopted in subsequent data processing are introduced and their practical applications in biosensors are reviewed. Finally, the challenges faced by machine learning‐reinforced biosensors are raised, including data privacy and adaptive learning capability, and their prospects in real‐time monitoring, out‐of‐clinic diagnosis, and onsite food safety detection are proposed.

show abstract

Improving the reproducibility, accuracy, and stability of an electrochemical biosensor platform for point-of-care use

Cited by 93 publications

References 32 publications

Metal Nanoparticles for Electrochemical Sensing: Progress and Challenges in the Clinical Transition of Point-of-Care Testing

Metal Nanoparticles for Electrochemical Sensing: Progress and Challenges in the Clinical Transition of Point-of-Care Testing

Electrochemical DNA Sensor for Sensitive BRCA1 Detection Based on DNA Tetrahedral-Structured Probe and Poly-Adenine Mediated Gold Nanoparticles

Machine Learning‐Reinforced Noninvasive Biosensors for Healthcare

Contact Info

Product

Resources

About