A high-performance electrochemical aptasensor based on graphene-decorated rhodium nanoparticles to detect HER2-ECD oncomarker in liquid biopsy

Sadeghi, Mahdi; Kashanian, Soheila; Naghib, Seyed Morteza; Arkan, Elham

doi:10.1038/s41598-022-07230-3

Cited by 44 publications

(16 citation statements)

References 67 publications

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“…Moreover, the advancement in nanostructured materials has attracted much attention in recent years due to their potential applications and unique properties, including high reactivity, high functionalization, large surface-area-to-volume ratio, and small size [ 5 ]. Thus, advanced nanostructured materials have been utilized to improve the sensing capacities of aptasensors [ 6 ], lower the limits of detection of analytes [ 7 ], and amplify the sensors’ signals [ 8 ]. Nanomaterial-based aptasensors have been used as effective instruments for recognizing small analytes in clinical health diagnostics [ 6 , 7 ], medical therapy [ 9 ], and disease biomarker detection [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, advanced nanostructured materials have been utilized to improve the sensing capacities of aptasensors [ 6 ], lower the limits of detection of analytes [ 7 ], and amplify the sensors’ signals [ 8 ]. Nanomaterial-based aptasensors have been used as effective instruments for recognizing small analytes in clinical health diagnostics [ 6 , 7 ], medical therapy [ 9 ], and disease biomarker detection [ 10 ]. In addition, using and improving these analytical devices for identifying and quantifying a target analyte is beneficial due to their having higher specificity and selectivity and their elimination of labor-intensive and time-consuming procedures, expensive instruments, and multiple analytical steps [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

et al. 2022

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Nanomaterial-based aptasensors are useful devices capable of detecting small biological species. Determining suitable signal processing methods can improve the identification and quantification of target analytes detected by the biosensor and consequently improve the biosensor’s performance. In this work, we propose a data augmentation method to overcome the insufficient amount of available original data and long short-term memory (LSTM) to automatically predict the analyte concentration from part of a signal registered by three electrochemical aptasensors, with differences in bioreceptors, analytes, and the signals’ lengths for specific concentrations. To find the optimal network, we altered the following variables: the LSTM layer structure (unidirectional LSTM (LSTM) and bidirectional LSTM (BLSTM)), optimizers (Adam, RMSPROP, SGDM), number of hidden units, and amount of augmented data. Then, the evaluation of the networks revealed that the highest original data accuracy increased from 50% to 92% by exploiting the data augmentation method. In addition, the SGDM optimizer showed a lower performance prediction than that of the ADAM and RMSPROP algorithms, and the number of hidden units was ineffective in improving the networks’ performances. Moreover, the BLSTM nets showed more accurate predictions than those of the ULSTM nets on lengthier signals. These results demonstrate that this method can automatically detect the analyte concentration from the sensor signals.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

et al. 2022

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“…T HE development of electrochemical biosensors has attracted considerable research efforts in the last years since they offer the possibility to solve the analytical requirements by using simple and highly sensitive devices [1], [2], [3], especially for clinical diagnostics [4], [5], [6] and agrifood quality analysis [7], [8]. Genosensors have a broad range of potential applications, providing simple, rapid, and economical assays for DNA diagnostics, gene analysis, and fast detection of pathogens [9].…”

Section: Introductionmentioning

confidence: 99%

Influence of BSA Protein on Electrochemical Response of Genosensors

Bonaldo

Franchin

Pasqualotto³

et al. 2023

IEEE Sensors J.

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The bovine serum albumin (BSA) protein is employed in genosensors as nonspecific binding blocker. In this work, the influence of BSA on the electrochemical response of a DNA-based biosensor is explored by electrochemical impedance spectroscopy (EIS) and double pulse voltammetry technique. Each buffer component of the hybridization buffer is studied on bare gold electrodes and on single-stranded DNA (ssDNA)-functionalized electrodes. The BSA is found to have the higher influence on the sensor sensitivity. The superficial modification induced by BSA greatly affects the electrochemical signal due to steric hindrance, which decreases the device sensitivity. Thus, we propose a novel treatment method of the BSA by using the proteinase K. The proteinase K reduces the steric hindrance, improving the charge transfer at the electrode/solution interface and enhancing the genosensor sensitivity. The proposed method is based on a rapid BSA treatment. The BSA solution containing the proteinase K is kept for 1 h at 37 • C to obtain BSA fragmentation and then heated up to 95 • C for 2 min to inactivate the enzyme and denature the fragments. The method was tested successfully on a genosensor for the detection of the Campylobacter Jejuni. Double pulse current measurements clearly discriminate the presence of complementary DNA (cDNA) fragments with any other noncomplementary DNA (NcDNA) fragments.

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“…On the other hand, the use of biosensors offers rapid, accurate, and on-site detection, performed even by non-specialized users [ 7 ]. Biosensors have attracted considerable research efforts in recent years such as in clinical diagnostics [ 8 , 9 , 10 ] and agri-food quality monitoring [ 11 , 12 ], allowing for the development of easily integrated systems to analyze biological samples directly at the point of care [ 13 , 14 , 15 ]. In particular, optical biosensors are considered valuable resources in clinical analysis since they allow for the detection and quantification of the presence of specific analytes in complex-matrix samples such as blood and urine, with high sensitivity, high rejection to external interferences, stability, and low noise [ 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Optical System Based on Nafion Membrane for the Detection of Ammonia in Blood Serum Samples

et al. 2022

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The blood ammonia (NH3) level is one of the most important hepatic biomarkers for the diagnosis and monitoring of liver pathologies and infections. In this work, we developed an optimized optical biosensing method to extract and quantify the ammonia contained in complex-matrix samples emulating the blood serum. First, the approach was tested with solutions of phosphate-buffered saline (PBS) and ammonia chloride. Then, further trials were carried out with solutions of fetal bovine serum (FBS). The ammonia was extracted from the tested samples through a customized cell, and it was optically quantified by exploiting the indophenol reaction. The extraction cell included a cation-exchange membrane in Nafion, which was chemically pre-treated through cleaning procedures of sulfuric acid and hydrogen peroxide to keep a basic pH in the ammonia solution and to avoid contaminants in the membrane. From the NH3 solution, the indophenol reaction produced light-reactive indophenol dye molecules, which were used as colorimetric indicators. Through absorbance measurements of the indophenol dye solution at 670 nm wavelength, we were able to detect and quantify the ammonia level in the samples both with a spectrophotometer and a customized miniaturized read-out system, obtaining a detection limit of 0.029 µmol/mL.

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A high-performance electrochemical aptasensor based on graphene-decorated rhodium nanoparticles to detect HER2-ECD oncomarker in liquid biopsy

Cited by 44 publications

References 67 publications

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

Influence of BSA Protein on Electrochemical Response of Genosensors

Optical System Based on Nafion Membrane for the Detection of Ammonia in Blood Serum Samples

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