Review · Micromachines · January 25, 2024
Hybrid Impedimetric Biosensors for Express Protein Markers Detection
Nikita O. Sitkov, Андрей Андреевич Рябко, Вячеслав Алексеевич Мошников, Andrey N. Aleshin, Dmitrii Kaplun, Tatiana M. Zimina
Abstract
Impedimetric biosensors represent a powerful and promising tool for studying and monitoring biological processes associated with proteins and can contribute to the development of new approaches in the diagnosis and treatment of diseases. The basic principles, analytical methods, and applications of hybrid impedimetric biosensors for express protein detection in biological fluids are described. The advantages of this type of biosensors, such as simplicity and speed of operation, sensitivity and selectivity of analysis, cost-effectiveness, and an ability to be integrated into hybrid microfluidic systems, are demonstrated. Current challenges and development prospects in this area are analyzed. They include (a) the selection of materials for electrodes and formation of nanostructures on their surface; (b) the development of efficient methods for biorecognition elements' deposition on the electrodes' surface, providing the specificity and sensitivity of biosensing; (c) the reducing of nonspecific binding and interference, which could affect specificity; (d) adapting biosensors to real samples and conditions of operation; (e) expanding the range of detected proteins; and, finally, (f) the development of biosensor integration into large microanalytical system technologies. This review could be useful for researchers working in the field of impedimetric biosensors for protein detection, as well as for those interested in the application of this type of biosensor in biomedical diagnostics.
More by Dmitry Kaplun
- Codewithsayanjib/slm-systematic-review: v1.1Zenodo · 2026
- Microscopy Image Dataset of pulmonary vessels for Quantitative assessment of fibrosisScientific Data · 2026
- Microscopy Image Dataset of pulmonary vessels for Deep Learning-Based Quantitative assessment of fibrosisFigshare · 2026
- MA2MU-Net++: A Mahalanobis distance and Ackley function based multi-modal U-Net++ model for breast nuclei segmentation in histopathology imagesBiomedical Signal Processing and Control · 2026
