Related Experiment Video For Conducting polymers
Updated: May 13, 2025

Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor
Published on: February 16, 2018
Molecular Imprinted Polymer Decorated Electrochemical Sensors for Diabetes Biomarkers: A Critical Review
Agraja P S1, Sreelekshmi P J1, Devika V1
1Department of Chemistry, Amrita Vishwa Vidyapeetham, Kollam, India.
Abstract:
Diabetes is a chronic illness marked by high blood sugar or hyperglycemia, which can be caused by deficiencies in the action or secretion of insulin, or both. A prolonged period of elevated blood glucose levels can cause several tissues to malfunction. To avoid or postpone the onset of problems associated with diabetes, early diagnosis, and effective care are essential. Biomarkers and biosensors have become potential tools for monitoring and managing diabetes. Glucose, glycated hemoglobin, and other relevant biomarkers of diabetes can be detected using various biosensors, including enzymatic, electrochemical, and optical types. The molecular imprinting technique is an emerging electroanalytical method, that creates cavities in the polymer matrix with an affinity for a selected template molecule, known as molecularly imprinted polymer (MIP). Typically, the procedure involves the polymerization of monomers in the presence of a template molecule, which is then removed to leave behind imprinting sites. These polymers have been employed in molecular sensors, chemical separations, and catalysis due to their affinity for the original molecule. With special attention to their mechanisms of action, clinical applications, limitations, and the potential of emerging technologies, such as wearables and nano-biosensors, these can be used for continuous and real-time diabetes monitoring. This critical review focuses on the role of nanomaterials and conducting polymer-decorated molecularly imprinted sensors for tracking diabetes biomarkers. Additionally, this paper discusses the difficulties in developing and implementing biosensors, including selectivity, sensitivity, and real-time monitoring of glucose levels.
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