Anna V. Shik

Dr. Anna V. Shik

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Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 February 2022 in Chemosensors
Verified
Journal Article
Open access
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ASAnna V. Shik
Anna V. Shik
ISIrina A. Stepanova
Irina A. Stepanova
IDIrina A. Doroshenko
Irina A. Doroshenko
PTPodrugina Tatyana
Podrugina Tatyana
Mikhail K. BeklemishevMikhail K. Beklemishev
Mikhail K. Beklemishev
Array-based optical sensing is an efficient technique for the determination and discrimination of small organic molecules. This study is aimed at the development of a simple and rapid strategy for obtaining an optical response from a wide range of low-molecular-weight organic compounds. We have suggested a colorimetric and fluorimetric sensing platform based on the combination of two response mechanisms using carbocyanine dyes: aggregation and oxidation. In the first one, the analyte forms ternary aggregates with an oppositely charged surfactant wherein the dye is solubilized in the hydrophobic domains of the surfactant accompanied with fluorescent enhancement. The second mechanism is based on the effect of the analyte on the catalytic reaction rate of dye oxidation with H2O2 in the presence of a metal ion (Cu2+, Pd2+), which entails fluorescence waning and color change. The reaction mixture in a 96-well plate is photographed in visible light (colorimetry) and the near-IR region under red light excitation (fluorimetry). In this proof-of-concept study, we demonstrated the feasibility of discrimination of nine medicinal compounds using principal component analysis: four cephalosporins (ceftriaxone, cefazolin, ceftazidime, cefotaxime), three phenothiazines (promethazine, promazine, chlorpromazine), and two penicillins (benzylpenicillin, ampicillin) in an aqueous solution and in the presence of turkey meat extract. The suggested platform allows simple and rapid recognition of analytes of various nature without using spectral equipment, except for a photo camera.

13 February 2023 in Food Chemistry
Verified
Journal Article
Closed access
ASAnna V. Shik
Anna V. Shik
ESEvgenii V. Skorobogatov
Evgenii V. Skorobogatov
UBUlyana Bliznyuk
Ulyana Bliznyuk
ACAlexander Petrovich Chernyaev
Alexander Petrovich Chernyaev
VAValentina M. Avdyukhina
Valentina M. Avdyukhina
Mikhail K. BeklemishevMikhail K. Beklemishev
Mikhail K. Beklemishev

26 April 2023 in Sensors
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Journal Article
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ASAnna V. Shik
Anna V. Shik
ISIrina A. Stepanova
Irina A. Stepanova
IDIrina A. Doroshenko
Irina A. Doroshenko
PTPodrugina Tatyana
Podrugina Tatyana
Mikhail K. BeklemishevMikhail K. Beklemishev
Mikhail K. Beklemishev
Optical sensor arrays are widely used in obtaining fingerprints of samples, allowing for solutions of recognition and identification problems. An approach to extending the functionality of the sensor arrays is using a kinetic factor by conducting indicator reactions that proceed at measurable rates. In this study, we propose a method for the discrimination of proteins based on their oxidation by sodium hypochlorite with the formation of the products, which, in turn, feature oxidation properties. As reducing agents to visualize these products, carbocyanine dyes IR-783 and Cy5.5-COOH are added to the reaction mixture at pH 5.3, and different spectral characteristics are registered every several minutes (absorbance in the visible region and fluorescence under excitation by UV (254 and 365 nm) and red light). The intensities of the photographic images of the 96-well plate are processed by principal component analysis (PCA) and linear discriminant analysis (LDA). Six model proteins (bovine and human serum albumins, γ-globulin, lysozyme, pepsin, and proteinase K) and 10 rennet samples (mixtures of chymosin and pepsin from different manufacturers) are recognized by the proposed method. The method is rapid and simple and uses only commercially available reagents.

31 March 2025 in Food Chemistry
Verified
Journal Article
Closed access
ASAnna V. Shik
Anna V. Shik
ISIrina A. Stepanova
Irina A. Stepanova
MKMarina V. Koksharova
Marina V. Koksharova
IDIrina A. Doroshenko
Irina A. Doroshenko
TPTatyana A. Podrugina
Tatyana A. Podrugina
MBMikhail K. Beklemishev
Mikhail K. Beklemishev

6 September 2023 in Sensors
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Journal Article
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APArseniy Pypin
Arseniy Pypin
ASAnna V. Shik
Anna V. Shik
ISIrina A. Stepanova
Irina A. Stepanova
IDIrina A. Doroshenko
Irina A. Doroshenko
PTPodrugina Tatyana
Podrugina Tatyana
Mikhail K. BeklemishevMikhail K. Beklemishev
Mikhail K. Beklemishev
Optical “fingerprints” are widely used for chemometrics-assisted recognition of samples of different types. An emerging trend in this area is the transition from obtaining “static” spectral data to reactions analyzed over time. Indicator reactions are usually carried out in aqueous solutions; in this study, we developed reactions that proceed in an organic solvent, thereby making it possible to recognize fat-soluble samples. In this capacity, we used 5W40, 10W40, and 5W30 motor oils from four manufacturers, with six samples in total. The procedure involved mixing a dye, sample, and reagents (HNO3, HCl, or tert-butyl hydroperoxide) in an ethanolic solution in a 96-well plate and measuring absorbance or near-infrared fluorescence intensity every several minutes for 20–55 min. The obtained photographic images were processed by linear discriminant analysis (LDA) and the k-nearest neighbors algorithm (kNN). Discrimination accuracy was evaluated by a validation procedure. A reaction of oxidation of a dye by nitric acid allowed us to recognize all six samples with 100% accuracy for LDA. Merging of data from the four reactions that did not provide complete discrimination ensured an accuracy of 93% for kNN. The newly developed indicator systems have good prospects for the discrimination of other fat-soluble samples. Overall, the results confirm the viability of the kinetics-based discrimination strategy.

9 July 2024 in Industrial & Engineering Chemistry Research
Verified
Journal Article
Closed access
ESEvgenii V. Skorobogatov
Evgenii V. Skorobogatov
ASAnna V. Shik
Anna V. Shik
PSPavel V. Sobolev
Pavel V. Sobolev
ISIrina A. Stepanova
Irina A. Stepanova
VOVladislav S. Orekhov
Vladislav S. Orekhov
Mikhail K. BeklemishevMikhail K. Beklemishev
Mikhail K. Beklemishev