The objective of the study has been the development of a new sensing platform, called Real-time Electrochemical Profiling (REP) that relies on real-time electrochemical immunoassay detection. The proposed REP platform consists of new electrode arrays that are easy to fabricate, has a small imprint allowing microfluidic system integration, enables multiplexed amperometric measurements and performs well in terms of electrochemical immunoassay detection as shown through the deoxynivalenol detection assays. The deoxynivalenol detection has been conducted according to an optimised REP assay protocol using deoxynivalenol standards at varying concentrations and a standard curve was obtained (y=-20.33ln(x)+124.06; R(2)=0.97) with a limit of detection of 6.25 ng/ml. As both ELISA and REP detection methods use horse radish peroxidase as the label and 3.3',5.5'-Tetramethylbenzidine as the substrate, the performance of the REP platform as an ELISA reader has also been investigated and a perfect correlation between the deoxynivalenol concentration and the current response was obtained (y=-14.56ln(x)+101.02; R(2)=0.99). The calibration curves of both assays have been compared to conventional ELISA tests for confirmation. After assay optimisation using toxin spiked buffer, the deoxynivalenol detection assay has also been performed to detect toxins in wheat grain.
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http://dx.doi.org/10.1016/j.bios.2014.06.025 | DOI Listing |
ACS Sens
January 2025
Department of Engineering Physics, McMaster University, 1280 Main Street West, L8S 4L8 Hamilton, Ontario, Canada.
Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.
View Article and Find Full Text PDFACS Phys Chem Au
January 2025
Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.
Neutron-Transformer Reflectometry Advanced Computation Engine (), a neural network model using a transformer architecture, is introduced for neutron reflectometry data analysis. It offers fast, accurate initial parameter estimations and efficient refinements, improving efficiency and precision for real-time data analysis of lithium-mediated nitrogen reduction for electrochemical ammonia synthesis, with relevance to other chemical transformations and batteries. Despite limitations in generalizing across systems, it shows promises for the use of transformers as the basis for models that could accelerate traditional approaches to modeling reflectometry data.
View Article and Find Full Text PDFFood Chem X
January 2025
Division of Biochemistry, ICAR-Indian Agricultural Research Institute (IARI), New Delhi 110012, India.
The accurate quantification of glycemic index (GI) remains crucial for diabetes management, yet current methodologies are constrained by resource intensiveness and methodological limitations. digestion models face challenges in replicating the dynamic conditions of the human gastrointestinal tract, such as enzyme variability and multi-time point analysis, leading to suboptimal predictive accuracy. This review proposes an integrated technological framework combining non-enzymatic electrochemical sensing with artificial intelligence to revolutionize GI assessment.
View Article and Find Full Text PDFACS Omega
January 2025
Department of Biomedical Engineering, Hanyang University, Seoul 04763, Republic of Korea.
Fast-scan cyclic voltammetry (FSCV) is a widely used electrochemical technique to measure the phasic response of neurotransmitters in the brain. It has the advantage of reducing tissue damage to the brain due to the use of carbon fiber microelectrodes as well as having a high temporal resolution (10 Hz) sufficient to monitor neurotransmitter release in vivo. During the FSCV experiment, the surface of the carbon fiber microelectrode is inevitably changed by the fouling effect.
View Article and Find Full Text PDFAnal Chem
January 2025
College of Chemistry, Beijing Normal University, Beijing 100875, China.
5-Hydroxyindoleacetic acid (5-HIAA), a vital metabolite of serotonin (5-HT), is crucial for understanding metabolic pathways and is implicated in various mental disorders. In situ monitoring of 5-HIAA is challenging due to the lack of affinity ligands and issues with electrochemical fouling. We present an advanced sensing approach that integrates customizable molecular imprinting polymer (MIP) with self-driven galvanic redox potentiometry (GRP) for precise, real-time in vivo monitoring of 5-HIAA.
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