Advances in electrochemical biosensor design for the detection of the stress biomarker cortisol

Weber, Courtney J.; Clay, Olivia M.; Lycan, Reese E.; Anderson, Gracie K.; Simoska, Olja

doi:10.1007/s00216-023-05047-1

Anal Bioanal Chem

2023

DOI: 10.1007/s00216-023-05047-1

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Advances in electrochemical biosensor design for the detection of the stress biomarker cortisol

Courtney J. Weber,

Olivia M. Clay,

Reese E. Lycan

et al.

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2024

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Cited by 5 publications

(1 citation statement)

References 126 publications

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“…Non-enzymatic and non-microbial recognition elements include other selective biological materials, such as aptamers or antibodies. 1,5 In terms of enzyme and microbebased EB designs, each recognition element is associated with distinct advantages, as well as challenges in device performance. Enzyme-based EBs offer high selectivity and sensitivity for target analytes.…”

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Perspective—Surface-display Techniques in Electrochemical Biosensor Designs for Health Monitoring

Weber,

Whisonant,

Clay

et al. 2024

ECS Sens. Plus

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Enzymatic and microbial electrochemical biosensors integrate enzymes and microorganisms as biological recognition elements into the sensor design and functionality. Enzyme-based sensors offer high sensitivity and selectivity for target analyte detection. However, these have limited stability necessary for continuous analyte monitoring. Contrarily, microbe-based electrochemical sensors provide a means for continuous analyte sensing but are associated with challenges related to analyte selectivity in complex samples. To address these limitations, surface-display methods, which bind enzymes to microbial surfaces, enhance biosensor selectivity and sensitivity. This perspective outlines the application of surface-display techniques, offering a promising avenue for health monitoring.

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Perspective—Surface-display Techniques in Electrochemical Biosensor Designs for Health Monitoring

Weber,

Whisonant,

Clay

et al. 2024

ECS Sens. Plus

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Enhancing electrochemical detection through machine learning-driven prediction for canine mammary tumor biomarker with green silver nanoparticles

Enginler,

Küçükdeniz,

Dal

et al. 2024

Anal Bioanal Chem

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This study developed an innovative biosensor strategy for the sensitive and selective detection of canine mammary tumor biomarkers, cancer antigen 15–3 (CA 15–3) and mucin 1 (MUC-1), integrating green silver nanoparticles (GAgNPs) with machine learning (ML) algorithms to achieve high diagnostic accuracy and potential for noninvasive early detection. The GAgNPs-enhanced electrochemical biosensor demonstrated selective detection of CA 15–3 in serum and MUC-1 in tissue homogenates, with limits of detection (LODs) of 0.07 and 0.11 U mL−1, respectively. The nanoscale dimensions of the GAgNPs endowed them with electrochemically active surface areas, facilitating sensitive biomarker detection. Experimental studies targeted CA 15–3 and MUC-1 biomarkers in clinical samples, and the biosensor exhibited ease of use and good selectivity. Furthermore, ML algorithms were employed to analyze the electrochemical data and predict biomarker concentrations, enhancing the diagnostic accuracy. The Random Forest algorithm achieved 98% accuracy in tumor presence prediction, while an Artificial Neural Network attained 76% accuracy in CA 15–3-based tumor grade classification. The integration of ML techniques with the GAgNPs-based biosensor offers a promising approach for noninvasive, accurate, and early detection of canine mammary tumors, potentially revolutionizing veterinary diagnostics. This multilayered strategy, combining eco-friendly nanomaterials, electrochemical sensing, and ML algorithms, holds significant potential for advancing both biomedical research and clinical practice in the field of canine mammary tumor diagnostics. Graphical Abstract

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Cortisol: Biosensing and detection strategies

Balasamy,

Atchudan,

Arya

et al. 2024

Clinica Chimica Acta

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Advances in electrochemical biosensor design for the detection of the stress biomarker cortisol

Cited by 5 publications

References 126 publications

Perspective—Surface-display Techniques in Electrochemical Biosensor Designs for Health Monitoring

Perspective—Surface-display Techniques in Electrochemical Biosensor Designs for Health Monitoring

Enhancing electrochemical detection through machine learning-driven prediction for canine mammary tumor biomarker with green silver nanoparticles

Cortisol: Biosensing and detection strategies

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