Kseniia Shestakova

Scopus Publications

Metabolomic profiling in cardio-oncology: current state of the problem and clinical perspectives
Creative Cardiology, 2026
Metabolomic profiling in heart failure as a new tool for diagnosis and phenotyping
Maria V. Kozhevnikova, Yuri N. Belenkov, Ksenia M. Shestakova, Anton A. Ageev, Pavel A. Markin, Anastasiia V. Kakotkina, Ekaterina O. Korobkova, Natalia E. Moskaleva, Ivan V. Kuznetsov, Natalia V. Khabarova, Alexey V. Kukharenko, Svetlana A. Appolonova
Scientific Reports, 2025
Classifying heart failure (HF) by stages and ejection fraction (EF) remains a debated topic in cardiology. Metabolomic profiling (MP) offers a means to identify unique pathophysiological changes across different phenotypes, presenting a promising approach for the diagnosis and prognosis of HF, as well as for the development of targeted therapies. In our study, MP was performed on 408 HF patients (54.9% male). The mean ages of patients were 62 [53;68], 67 [65;74], 68 [61;72], and 69 [65;73] years for stages A, B, C, and D, respectively. This study demonstrates high accuracy in HF stage classification, distinguishing Stage A from Stage B with an AUC ROC of 0.91 and Stage B from Stage C with an AUC ROC of 0.97, by integrating chromatography-mass spectrometry data through multiparametric machine learning models. The observed metabolic similarities between HF with mildly reduced EF and HF with reduced EF phenotypes (AUC ROC 0.96) once again highlight the fundamental differences at the cellular and molecular levels between HF with preserved EF and HF with EF < 50%. Hierarchical clustering based on MP identified four distinct HF phenotypes and 26 key metabolites, including metabolites of tryptophan catabolism, glutamine, riboflavin, norepinephrine, serine, and long- and medium-chain acylcarnitines. The average follow-up period was 542.37 [16;1271] days. A downward change in the trajectory of EF [HR 3,008, 95% CI 1,035 to 8,743, p = 0,043] and metabolomic cluster 3 [HR 2,880; 95% CI 1,062 to 7,810, p = 0,0376] were associated with increased risk of all-cause mortality. MP can refine HF phenotyping and deepen the understanding of its underlying mechanisms. Metabolomic analysis illuminates the biochemical landscape of HF, aiding in its classification and suggesting new therapeutic pathways.
Targeted metabolomics for cardiovascular disease: Validation of a high-throughput HPLC-MS/MS assay
Sabina N. Baskhanova, Natalia E. Moskaleva, Ksenia M. Shestakova, Maria V. Kozhevnikova, Ekaterina O. Korobkova, Victor M. Samoylov, Svetlana A. Appolonova
Journal of Chromatography B Analytical Technologies in the Biomedical and Life Sciences, 2025
Metabolomic Profiling as a Possible New Method For Predicting Cardiovascular Toxicity of Chemotherapy: a Pilot Single-Center Study
Yu. Yu. Kirichenko, V. G. Varsieva, Ksenia M. Shestakova, A. D. Chernichkina, A. V. Palienko, et al.
Kardiologiia, 2025
Aim To determine the array of metabolomic profiles and structural and functional parameters of the vascular wall associated with the risk of cardiovascular toxicity of antitumor therapy (ATT) in oncohematological patients.Material and methods This study included 59 patients, among them 34 patients with lymphomas (non-Hodgkin and Hodgkin lymphoma) and 25 with multiple myeloma. Before and after 3 courses of ATT (anthracyclines, proteasome inhibitors), finger photoplethysmography and transthoracic echocardiography were performed as well as metabolomic profiling (98 metabolites) by high-performance liquid chromatography in combination with tandem mass spectrometry. Statistical analysis of the results included parametric and nonparametric tests, logistic regression, and cross-validation.Results The study showed that even before the initiation of ATT, cancer patients had signs of endothelial dysfunction and increased vascular wall stiffness (increased aSI, RI, and IO indices), which significantly worsened after the specific treatment. Metabolomic profiling identified a set of metabolites associated with the risk of cardiovascular toxicity, including increased concentrations of amino acids (asparagine, serine, glutamate, glutamine, taurine, citrulline), short-chain acylcarnitines (C18:1 OH-carnitine, C16:1 OH-carnitine, C14OH-carnitine, C2 carnitine), choline metabolism intermediates (TMAO, dimethylglycine, choline), tryptophan metabolites (hydroxyindoleacetic acid, kynurenic acid). Additionally, a logistic regression model was developed based on the analysis of the metabolomic profile, which showed a high prognostic power (AUC = 0.84) for predicting cardiovascular toxicity of ATT.Conclusion The study identified key metabolites and structural and functional parameters of blood vessels that allow detection of an increased risk of cardiovascular complications of ATT in patients with lymphomas and multiple myeloma before the initiation of a specific treatment. Increased concentrations of amino acids, acylcarnitines, and choline metabolites may serve as an additional risk factor for the onset/progression of cardiovascular complications. The proposed integrative approach, including both metabolomic profiling and non-invasive assessment of the vascular wall condition, opens broad prospects for personalized cardioprotection of cancer patients and more accurate monitoring of the cardiovascular status during ATT.
Evaluating treatment responsiveness in rheumatoid arthritis through predictive metabolomic profiling: A systematic review of studies examining methotrexate, TNF, and IL-6 inhibitors as therapeutic interventions
Larisa M. Musaeva, Ksenia M. Shestakova, Sabina N. Baskhanova, Valeria G. Varzieva, Alex Brito, Irina Menshikova, Svetlana A. Appolonova
Clinical Rheumatology, 2025
Metabolomic Panel for the Diagnosis of Heart Failure with Preserved Ejection Fraction
Maria V. Kozhevnikova, Anastasiia V. Kakotkina, Ekaterina O. Korobkova, Ivan V. Kuznetsov, Ksenia M. Shestakova, Natalia E. Moskaleva, Svetlana A. Appolonova, Yuri N. Belenkov
International Journal of Molecular Sciences, 2025
The diagnosis of heart failure with preserved ejection fraction (HFpEF) remains challenging. The use of metabolomics approaches seems promising in speeding up and simplifying the diagnostic process in HFpEF patients, which can lead to earlier treatment initiation and better improvement of patient condition. The aim of this study was to develop a diagnostic panel of metabolites (metabolomic biomarkers) for the detection and diagnosis of HF with preserved ejection fraction. The study included 76 participants with hypertension, 36 of whom were diagnosed with HFpEF. The blood plasma metabolomic profile, including 72 metabolites, was detected using high-performance liquid chromatography combined with mass spectrometry. There were 18 statistically significant differences in concentrations of metabolites and 3 differences in their ratios between HFpEF and hypertension groups. The prognostic model for detecting the possibility of HFpEF included seven metabolites and two ratios: hexadecenoylcarnitine, arginine, trimethylamine-N-oxide, asymmetric dimethylarginine (ADMA), arginine/ADMA ratio, kynurenine, kynurenine/tryptophan, neopterin, and anthranilic acid. The area under the ROC curve was 0.981 ± 0.017. The resulting model was statistically significant (p < 0.001). The metabolomic panel could be considered as an addition to the present HFpEF laboratory diagnostic criteria for blood plasma analysis in clinical practice.
Targeted metabolomic profiling of human plasma by HPLC– MS/MS: optimization of sample preparation and automation of data processing
Sabina N. Baskhanova, Natal’ya E. Moskaleva, Kseniya M. Shestakova, Pavel A. Markin, Svetlana A. Apollonova
Analitika I Kontrol, 2025
Multitargeted metabolomic analysis is an effective tool for clinical diagnostics, which allows simultaneous profiling of a wide range of metabolites. The aim of the present study was developing and validating a method for targeted metabolomic profiling of blood plasma samples using HPLC-MS/MS and MS/MS methods. Sample preparation, derivatization conditions, and chromatographic–mass spectrometric detection parameters were optimized. Validation of the method was performed in accordance with the Guidelines for Interstate Standardization RMG 61-2010 and the ICH M10 Guideline on Bioanalytical Method Validation for Endogenous Compounds. A software application, Metaboscan AI, was developed to enhance the reliability of processing results of multitargeted data analysis. This tool automates data handling, including peak integration, concentration calculation, and quality control. For cohort studies, the application also supports comparative statistical analysis. The use of tools like multiple linear regression allows the assessment of the effect of biological cofactors (sex and age), thereby improving the interpretability of the results.
PreKinetix: web application for pharmacokinetic analysis in preclinical drug research
P. M Rezvanov, N. E. Moskaleva, K. M. Shestakova, V. V. Tarasov, E. A. Smolyarchuk, D. A. Kudlay, S. A. Apollonova
Farmatsiya I Farmakologiya, 2025
The aim. Development and validation of domestic software for non-compartmental analysis (NCA) of pharmacokinetic data, comparable in accuracy and functionality to the recognized foreign software Phoenix WinNonlin (USA).Materials and methods. The PreKinetix web application is implemented in the Python programming language using the Streamlit framework. Algorithms for calculating pharmacokinetic parameters (maximum concentration [Cmax], area under the pharmacokinetic curve [AUC], half-life [T1/2], mean residence time [MRT], etc.) are based on the methods of the reference software Phoenix WinNonlin (Certara, USA), used for comparison and are widely used in international practice. Three models of single drug administration are supported: intravenous bolus, intravenous infusion, and extravascular administration. Literary and experimental data covering more than 450 pharmacokinetic profiles were used for verification.Results. Calculations performed using PreKinetix showed complete agreement with the results of Phoenix WinNonlin with a relative error of less than 0.0001% for all main parameters. The program stably processes zero and missing values, automatically excludes incorrect records, visualizes pharmacokinetic profiles in linear and semi-logarithmic scales, and generates reports in .xlsx* and .docx* formats. The application interface allows it to be used not only by specialists but also by less trained users.Conclusion. PreKinetix is a domestic tool for NCA that combines accuracy, automation, accessibility, and convenience. It can be used in preclinical and early phases of clinical trials, as well as in educational settings for training specialists in pharmacokinetics and biopharmaceutics.
Targeted metabolomic profiling of multiple myeloma: diagnostics and treatment efficacy
V. G. Varzieva, K. M. Shestakova, A. A. Boldin, D. A. Kutsakina, Yu. Yu. Kirichenko, Yu. N. Belenkov, I. S. Ilgisonis, V. V. Tarasov, S. A. Appolonova
Drug Development and Registration, 2025
Introduction. Multiple myeloma (MM) is a malignant disease of plasma cells characterized by marked heterogeneity of the clinical course and variability in response to treatment. Metabolomic analysis, which reflects the totality of small molecules in biological fluids, opens up new possibilities for the search for diagnostic and prognostic biomarkers. Aim. To evaluate metabolomic profiles of patients with multiple myeloma (MM) and to identify metabolic markers associated with the efficacy of polychemotherapy. Materials and methods. The study was conducted from September 2022 to May 2025 at the Department of Hospital Therapy No. 1 of Sechenov University. We performed targeted analysis of plasma metabolites in 29 pre-treatment MM patients and 30 healthy volunteers (controls). Patients were divided into response and no response groups based on the results of therapy with VCD protocol after three courses. Results and discussion. Significant differences in metabolomic profiles of MM patients compared to controls were found. MM patients showed increased tryptophan catabolism via the kynurenine pathway (~41 % increase in kynurenine/tryptophan ratio, ~80 % decrease in serotonin levels), changes in urea and nitric oxide cycle metabolites (~28 % decrease in arginine, ~5.3-fold increase in asymmetric dimethylarginine), and amino acid imbalances (decrease in serine, aspartate, BCAA) and a significant increase in total acylcarnitines (~1.4-fold higher than control). The baseline metabolic profile also differed between patients with different treatment outcomes: before treatment, patients who subsequently showed a clinical response had lower levels of several acylcarnitines and tryptophan breakdown products (e.g. anthranilic acid), whereas patients without response showed decreased levels of 5-hydroxytryptophan, indole-3-lactic acid and histidine. Conclusions. Metabolomic analysis revealed characteristic metabolic alterations in MM reflecting activation of immunometabolic pathways (tryptophan kynurenine pathway, arginine metabolism) and impaired energy and amino acid regulation. The results indicate the potential prognostic significance of metabolites: a number of biomarkers (e.g. tryptophan derivatives, acylcarnitines) may be associated with chemotherapy sensitivity. The findings open the prospects for further research on metabolic approaches in MM monitoring and therapy.
Metabolomic Profiling of Patients with Alcoholic Liver Disease and Non-Alcoholic Fatty Liver Disease Using Principal Component Analysis
M. S. Reshetova, P. A. Markin, S. A. Appolonova, K. M. Shestakova, O. A. Baydalin, I. A. Voloshin, I. R. Yunusov, O. Yu. Zolnikova, R. V. Maslennikov, M. S. Zharkova, V. T. Ivashkin
Russian Journal of Gastroenterology Hepatology Coloproctology, 2025
Aim: to investigate the metabolomic profile of patients with alcoholic liver disease and non-alcoholic fatty liver disease.Materials and methods. The present study included patients diagnosed with non-alcoholic fatty liver disease (NAFLD) (n = 44), patients diagnosed with alcoholic liver disease (ALD) (n = 40) and 14 healthy volunteers. The level of metabolites in the blood serum were determined via high-performance liquid chromatography and tandem mass spectrometry.Results. In this study, a cross-sectional targeted metabolomic analysis of 96 serum metabolites was performed in patients. Statistical analysis using the principal component method identified six main factors, comprising metabolites from various metabolic pathways. Comparative analysis between patient groups and the control group revealed statistically significant differences in the metabolic activity of individual factors, collectively reflecting alterations in the metabolomic profile. Levels of acylcarnitines, uridine, metanephrine, asymmetric and total dimethylarginine were elevated in patients with NAFLD and ALD compared to the control group. Carnitine, short chain acylcarnitines, valine, leucine, lysine, and alanine were significantly higher in patients with NAFLD compared to those with ALD. In contrast, levels of tyrosine, epinephrine, and methionine were significantly increased in ALD patients compared to both NAFLD patients and healthy volunteers. Among patients with liver cirrhosis (both ALD and NAFLD), there was a noticeable trend toward altered metabolic activity of factors correlating with liver failure indicators and the FIB-4 index. As liver cirrhosis progressed, statistically significant changes in metabolite levels were observed across Child — Pugh classes, taking into account hypocoagulation, hypoalbuminemia, hyperbilirubinemia, the presence of ascites, and hepatic encephalopathy.
Changes in the metabolomic profile of blood plasma in patients with lymphoma during polychemotherapy
Valeria G. Varzieva, Andrey A. Boldin, Kseniia M. Shestakova, Sabina N. Baskhanova, Viktor M. Samoylov, Irina S. Ilgisonis, Yulia Yu. Kirichenko, Ramzullo R. Karimov, Elena A. Smolyarchuk, Dmitry A. Kudlay, Vadim V. Tarasov, Yuri N. Belenkov, Svetlana A. Appolonova
Terapevticheskii Arkhiv, 2025
A novel preliminary metabolomic panel for IHD diagnostics and pathogenesis
S. S. Markin, E. A. Ponomarenko, Yu. A. Romashova, T. O. Pleshakova, S. V. Ivanov, F. N. Bedretdinov, S. L. Konstantinov, A. A. Nizov, A. G. Koledinskii, A. I. Girivenko, K. M. Shestakova, P. A. Markin, N. E. Moskaleva, M. V. Kozhevnikova, Zh. Yu. Chefranova, S. A. Appolonova
Scientific Reports, 2024
Targeted metabolomic profiling of acute ST-segment elevation myocardial infarction
Sergey S. Markin, E. A. Ponomarenko, Yu. A Romashova, T. O. Pleshakova, S. V. Ivanov, V. V. Beregovykh, S. L. Konstantinov, G. I. Stryabkova, Zh. Yu. Chefranova, Y. A. Lykov, I. M. Karamova, A. G. Koledinskii, K. M. Shestakova, P. A. Markin, N. E. Moskaleva, S. A. Appolonova
Scientific Reports, 2024
Threonine in different phenotypes of chronic heart failure with preserved ejection fraction
Petrukhnova Maria F., Krivova Anastasia V., Zektser Vita Yu., Korobkova Ekaterina O., Edniev Tamerlan N., Ageev Anton A., Shestakova Ksenia M., Moskaleva Natalya E., Appolonova Svetlana A., Belenkov Yury N., Kozhevnikova Maria V.
Russian Open Medical Journal, 2024
Metabolomic changes in rheumatoid arthritis: focus on biological disease-modifying antirheumatic drugs
Larisa M. Musaeva, I. V. Menshikova, Svetlana A. Appolonova, Ksenya M. Shestakova
Clinical Review for General Practice, 2024
SOME FEATURES OF THE RELATIONSHIP OF AGE AND PHYSICAL QUALITIES: ANALYSIS OF IMPLEMENTATION GTO COMPLEX
Teoriya I Praktika Fizicheskoy Kultury, 2024
Metabolomic profiling in patients with rheumatoid arthritis (a pilot study)
Larisa M. Musaeva, , Irina V. Menshikova, Svetlana A. Appolonova, Ksenya M. Shestakova, , , and
Clinical Review for General Practice, 2024
Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer
Ksenia M. Shestakova, Natalia E. Moskaleva, Andrey A. Boldin, Pavel M. Rezvanov, Alexandr V. Shestopalov, Sergey A. Rumyantsev, Elena Yu. Zlatnik, Inna A. Novikova, Alexander B. Sagakyants, Sofya V. Timofeeva, Yuriy Simonov, Sabina N. Baskhanova, Elena Tobolkina, Serge Rudaz, Svetlana A. Appolonova
Scientific Reports, 2023
Relationship of Acylcarnitines to Myocardial Ischemic Remodeling and Clinical Manifestations in Chronic Heart Failure
Yuri N. Belenkov, Anton A. Ageev, Maria V. Kozhevnikova, Natalia V. Khabarova, Anastasia V. Krivova, Ekaterina O. Korobkova, Ludmila V. Popova, Alexey V. Emelyanov, Svetlana A. Appolonova, Natalia E. Moskaleva, Ksenia M. Shestakova, Elena V. Privalova
Journal of Cardiovascular Development and Disease, 2023
Metabolomics of head and neck cancer in biofluids: an integrative systematic review
Natalia Chuchueva, Filippo Carta, Hoang N. Nguyen, Jennifer Luevano, Isaiah A. Lewis, Israel Rios-Castillo, Vassilios Fanos, Emma King, Valery Swistushkin, Igor Reshetov, Yury Rusetsky, Ksenia Shestakova, Natalia Moskaleva, Cinzia Mariani, Alvaro Castillo-Carniglia, Dmitry Grapov, Johannes Fahrmann, Michael R. La Frano, Roberto Puxeddu, Svetlana A. Appolonova, Alex Brito
Metabolomics, 2023
Anthropogenic Neighborhood Impact on Bacterial and Fungal Communities in Polar Bear Feces
Maksim V. Vecherskii, Tatiana A. Kuznetsova, David R. Khayrullin, Aleksandr A. Stepankov, Svetlana M. Artemieva, Pavel V. Chukmasov, Evgeny A. Ivanov, Ivan A. Mizin, Ilya N. Mordvintsev, Nikita G. Platonov, Aleksandr A. Pashali, Artem I. Isachenko, Renata E. Lazareva, Ksenia M. Shestakova, Viatcheslav V. Rozhnov
Animals, 2023
Plasma branched-chain amino acid concentrations in individuals without cardiovascular diseases versus patients diagnosed with hypertension and coronary artery disease
M. V. Kozhevnikova, E. O. Korobkova, A. V. Krivova, A. V. Kukharenko, N. E. Moskaleva, K. M. Shestakova, N. V. Mesonzhnik, A. A. Ageev, A. A. Boldin, A. Brito, S. А. Appolonova, E. V. Privalova, Y. N. Belenkov
Rational Pharmacotherapy in Cardiology, 2023
Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults
Natalia E. Moskaleva, Ksenia M. Shestakova, Alexey V. Kukharenko, Pavel A. Markin, Maria V. Kozhevnikova, Ekaterina O. Korobkova, Alex Brito, Sabina N. Baskhanova, Natalia V. Mesonzhnik, Yuri N. Belenkov, Natalia V. Pyatigorskaya, Elena Tobolkina, Serge Rudaz, Svetlana A. Appolonova
Metabolites, 2022
A novel high-throughput liquid chromatography assay for Carbohydrate-Deficient transferrin (CDT) based on flow-modulated isocratic elution and terbium-induced fluorescence
Giacomo Musile, Elio Franco De Palo, Romolo Marco Dorizzi, Kseniia Shestakova, Svetlana Appolonova, Franco Tagliaro
Journal of Chromatography B Analytical Technologies in the Biomedical and Life Sciences, 2021
Pharmacokinetic properties of the novel synthetic cannabinoid 5f-apinac and its influence on metabolites associated with neurotransmission in rabbit plasma
Ksenia M. Shestakova, Natalia V. Mesonzhnik, Pavel A. Markin, Natalia E. Moskaleva, Andrey A. Nedorubov, Alex Brito, Elizaveta G. Appolonova, Roman M. Kuznetsov, Natalia L. Bochkareva, Alexey Kukharenko, Alexey V. Lyundup, Franco Tagliaro, Svetlana A. Appolonova
Pharmaceuticals, 2021
In Vivo Targeted Metabolomic Profiling of Prostanit, a Novel Anti-PAD NO-Donating Alprostadil-Based Drug
Ksenia M. Shestakova, Natalia E. Moskaleva, Natalia V. Mesonzhnik, Alexey V. Kukharenko, Igor V. Serkov, Igor I. Lyubimov, Elena V. Fomina-Ageeva, Vladimir V. Bezuglov, Mikhail G. Akimov, Svetlana A. Appolonova
Molecules, 2020
A simple and robust method for broad range screening of hair samples for drugs of abuse using a high-throughput UHPLC-Ion Trap MS instrument
Giacomo Musile, Mara Mazzola, Ksenia Shestakova, Sergey Savchuk, Svetlana Appolonova, Franco Tagliaro
Journal of Chromatography B Analytical Technologies in the Biomedical and Life Sciences, 2020
Fast hplc-ms/ms screening method for identification of illegal drugs including new psychoactive substances and their metabolites in human urine
S.A. Savchuk, K.M. Shestakova, L.N. Rizvanova, D.A. Burmykin, M.V. Ovcharov, N.V. Mesonzhnik, S.A. Appolonova
Sudebno Meditsinskaya Ekspertiza, 2020
In vivo and in vitro metabolism of the novel synthetic cannabinoid 5F-APINAC
Svetlana A. Appolonova, Covadonga Palacio, Ksenia M. Shestakova, Natalia V. Mesonzhnik, Alex Brito, Roman M. Kuznetsov, Pavel A. Markin, Natalia L. Bochkareva, Dmitry Burmykin, Maxim Ovcharov, Giacomo Musile, Franco Tagliaro, Sergey A. Savchuk
Forensic Toxicology, 2020
Thanatochemistry at the crime scene: a microfluidic paper-based device for ammonium analysis in the vitreous humor
Giacomo Musile, Yvane Agard, Elio F. De Palo, Ksenia Shestakova, Federica Bortolotti, Franco Tagliaro
Analytica Chimica Acta, 2019
A novel low-cost approach for the semi-quantitative analysis of carbohydrate-deficient transferrin (CDT) based on fluorescence resonance energy transfer (FRET)
Giacomo Musile, Elio Franco De Palo, Sergey Alexandrovich Savchuk, Ksenia Shestakova, Federica Bortolotti, Franco Tagliaro
Clinica Chimica Acta, 2019
A new method for the determination of ammonium in the vitreous humour based on capillary electrophoresis and its preliminary application in thanatochemistry
Rossella Gottardo, Covadonga Palacio, Kseniia M. Shestakova, Natalia E. Moskaleva, Federica Bortolotti, Franco Tagliaro
Clinical Chemistry and Laboratory Medicine, 2019
Development of a low cost gas diffusion device for ammonia detection in the vitreous humor and its preliminary application for estimation of the time since death
Giacomo Musile, Rossella Gottardo, Covadonga Palacio, Ksenia Shestakova, Dario Raniero, Elio F. De Palo, Franco Tagliaro
Forensic Science International, 2019
Development and application of a rapid screening method for determination of new psychoactive substances and their metabolites in urine
Periodico Tche Quimica, 2019
Rabbit plasma metabolomic analysis of Nitroproston®: a multi target natural prostaglandin based-drug
Ksenia Shestakova, Alex Brito, Natalia V. Mesonzhnik, Natalia E. Moskaleva, Ksenia O. Kurynina, Natalia M. Grestskaya, Igor V. Serkov, Igor I. Lyubimov, Vladimir V. Bezuglov, Svetlana A. Appolonova
Metabolomics, 2018
LC-MS/MS identification and structural characterization of main biodegradation products of nitroproston-A novel prostaglandin-based pharmaceutical compound
Natalia V. Mesonzhnik, Natalia E. Moskaleva, Ksenia M. Shestakova, Ksenya O. Kurynina, Pavel A. Baranov, Natalia M. Gretskaya, Igor V. Serkov, Igor I. Lyubimov, Vladimir V. Bezuglov, Svetlana A. Appolonova
Drug Metabolism Letters, 2018
Procedure for setting control for the turnover of new, potentially hazardous psychoactive substances. Detection of metabolites of a new APINAC psychoactive compound in rat urine by gas and liquid chromatography with mass spectrometry detection
S. A. Savchuk, S. A. Appolonova, O. M. Kogdas’, V. N. Unizhaev, O. S. Gorina, L. N. Rizvanova, N. V. Samyshkina, K. M. Shestakova
Journal of Analytical Chemistry, 2017
In vivo metabolism of the new synthetic cannabinoid APINAC in rats by GC–MS and LC–QTOF-MS
Sergey Savchuk, Svetlana Appolonova, Alexander Pechnikov, Liliay Rizvanova, Ksenia Shestakova, Franco Tagliaro
Forensic Toxicology, 2017

Kseniia Shestakova

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