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Sergey A. Piletsky

Researcher at University of Leicester

Publications -  375
Citations -  18525

Sergey A. Piletsky is an academic researcher from University of Leicester. The author has contributed to research in topics: Molecularly imprinted polymer & Molecular imprinting. The author has an hindex of 66, co-authored 355 publications receiving 16194 citations. Previous affiliations of Sergey A. Piletsky include University of Bedfordshire & Cranfield University.

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Analytical methods for determination of mycotoxins: A review

TL;DR: This review manuscript discusses sample pre-treatment methods such as liquid-liquid extraction, supercritical fluid extraction, solid phase extraction, and others such as ELISA and further currents trends, advantages and disadvantages and future prospects of these methods have been discussed.
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The rational development of molecularly imprinted polymer-based sensors for protein detection.

TL;DR: This critical review describes many methods used for imprinting recognition for protein targets in polymers and their incorporation with a number of transducer platforms with the aim of identifying the most promising approaches for the preparation of MIP-based protein sensors.
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Molecularly Imprinted Polymers in Electrochemical and Optical Sensors

TL;DR: This review aims to provide a focused overview of the latest achievements made in MIP-based sensor technology, with emphasis on research toward real-life applications.
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Electrochemical Sensor for Catechol and Dopamine Based on a Catalytic Molecularly Imprinted Polymer-Conducting Polymer Hybrid Recognition Element

TL;DR: The preparation and characterization of novel hybrid materials combining a catalytic MIP, capable of oxidizing the template, catechol, with an electrically conducting polymer, and the catalytic properties of the sensor were characterized by chronoamperometry and were found to be consistent with Michaelis-Menten kinetics.
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Surface-Grafted Molecularly Imprinted Polymers for Protein Recognition

TL;DR: Easy preparation of the MIPs, their high stability, and their ability to recognize small and large proteins, as well as to discriminate molecules with small variations in charge, make this approach attractive and broadly applicable in biotechnology, assays and sensors.