Vladimir Borisovich Betelin

Interstitial lung diseases (ILDs) comprise a heterogeneous group of diffuse parenchymal lung disorders requiring accurate non-invasive diagnostic approaches. This study evaluated real-time proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) combined with machine learning for breath-based ILD detection and characterization. Overall, 251 patients with ILD and 251 healthy controls underwent analysis of volatile organic compounds (VOCs) during normal quiet breathing and forced expiration. The ILD cohort comprised multiple clinically heterogeneous ILD subtypes. Gradient boosting models were evaluated using repeated Monte Carlo cross-validation, with additional age- and sex-matched validation, ILD subtype classification, and kernel canonical correlation analysis (KCCA). Models incorporating VOCs and demographic variables achieved AUCs of 0.900 and 0.897 for normal and forced breathing, respectively, while VOC-only models retained good discrimination (AUC 0.874 and 0.875). Four VOC-related ions (m/z 55.03859, 63.01996, 90.95284, and 107.0886) were reproducibly identified. Discrimination among individual ILD subtypes was modest, with the highest AUC observed for IPF (0.709). KCCA demonstrated significant associations between VOC signatures and clinical-functional impairment under both breathing conditions. These findings support PTR-TOF-MS breath analysis as a promising non-invasive approach for ILD detection, while subtype classification and disease severity assessment require further independent validation.

Chronic obstructive and inflammatory lung diseases share overlapping clinical manifestations and spirometric features, complicating differential diagnosis and monitoring. In this study, we performed an integrative real-time proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) breathomics analysis to assess whether exhaled volatile organic compound (VOC) profiles enable multiclass discrimination among bronchial asthma (BA), chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF), and lymphangioleiomyomatosis (LAM), with healthy individuals as controls. Breath VOC data from 843 subjects were analyzed using a stratified 70/30 train/test split. An ensemble feature selection strategy based on gradient boosting (XGBoost with SMOTE within cross-validation) identified stable VOC panels (top 25% selection probability), yielding 29 VOCs and 31 features including clinical covariates. On the independent test set, the VOC-only model achieved a macro-averaged one-vs-one (OvO) AUC of 0.866 (95% CI 0.829–0.903), while the combined model improved to 0.888 (95% CI 0.853–0.919), indicating modest value of clinical variables. Pairwise analysis demonstrated highest discrimination for CF (AUC up to 0.988), whereas BA and LAM showed lower sensitivity (<0.60), likely reflecting heterogeneity and limited sample size. Given differences in age, sex, BMI, and smoking status across cohorts, confounding effects were assessed, confirming that VOC signatures retain independent diagnostic information. Disease-specific VOC interaction networks revealed distinct remodeling patterns, with central metabolites not captured by univariate analysis. Overall, PTR-TOF-MS breathomics demonstrates proof-of-concept multiclass discrimination across chronic lung diseases.

Malignant neoplasms remain one of the leading causes of death worldwide, continuously driving the development and active implementation of new innovative treatments into clinical practice. This article provides a comprehensive review of the current status and prospects for the application of mRNA technologies in oncology, analyzing global clinical trial experience, the mechanism of action of therapeutic mRNA cancer vaccines, manufacturing processes, and the regulatory framework for the introduction of individual biotechnologically modified drugs (iBTMD) in the Russian Federation.

Background: Asthma and chronic obstructive pulmonary disease (COPD) are prevalent obstructive lung diseases with distinct inflammatory pathways but overlapping clinical features. Bronchodilator responsiveness (BDR) is a key diagnostic criterion, yet its metabolic determinants are poorly understood. Objective: This cross-sectional study investigated whether integrated profiling of exhaled volatile organic compounds (VOCs) and clinical biomarkers can differentiate BA, COPD, and health, and predict BDR. Methods: Exhaled breath from 160 BA patients, 128 COPD patients, and 254 healthy controls was analyzed in real-time using proton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) during tidal and forced expiration. Clinical assessment included spirometry, fractional exhaled nitric oxide (FeNO), blood eosinophil count, and total IgE. Machine-learning (XGBoost) was employed for feature selection and model development. Results: Distinct VOC signatures effectively discriminated disease groups from controls and from each other. The model for distinguishing asthma from healthy controls achieved an AUC of 0.747 during normal quiet breathing and 0.710 during forced exhale. For discriminating COPD from healthy controls, the model performance was higher, with an AUC of 0.821 for normal quiet breathing and 0.856 for forced exhale. A model integrating VOC profiles with clinical biomarkers (FeNO, eosinophils, IgE) demonstrated very high accuracy in internal validation in predicting BDR (AUC = 1.000 for tidal breathing; AUC = 0.970 for forced expiration). Specific mass spectral features (m/z 79, m/z 101) were significantly associated with a positive BDR test. Conclusions: This study delineates disease-specific VOC signatures and underscores the profound synergy between exhaled metabolomics and clinical immunology for identifying associations treatment response, advocating for the integration of real-time breath analysis into personalized management strategies for obstructive lung diseases.

Lymphangioleiomyomatosis (LAM) is a rare progressive disease that affects women of reproductive age and is characterized by cystic lung destruction, airflow obstruction, and lymphatic dysfunction. Current diagnostic methods are costly or lack sufficient specificity, highlighting the need for novel non-invasive approaches. Exhaled breath analysis using real-time proton mass spectrometry (PTR-MS) presents a promising strategy for identifying disease-specific volatile organic compounds (VOCs). This cross-sectional study analyzed exhaled breath samples from 51 LAM patients and 51 age- and sex-matched healthy controls. PTR-time-of-flight mass spectrometry (PTR-TOF-MS) was employed to identify VOC signatures associated with LAM. Data preprocessing, feature selection, and statistical analyses were performed using machine learning models, including gradient boosting classifiers (XGBoost), to identify predictive biomarkers of LAM and its complications. We identified several VOCs as potential biomarkers of LAM, including m/z = 90.06 (lactic acid) and m/z = 113.13. VOCs predictive of disease complications included m/z = 49.00 (methanethiol), m/z = 48.04 (O-methylhydroxylamine), and m/z = 129.07, which correlated with pneumothorax, obstructive ventilation disorders, and radiological findings of lung cysts and bronchial narrowing. The classifier incorporating these biomarkers demonstrated high diagnostic accuracy (AUC = 0.922). This study provides the first evidence that exhaled breath VOC profiling can serve as a non-invasive additional tool for diagnosing LAM and predicting its complications. These findings warrant further validation in larger cohorts to refine biomarker specificity and explore their clinical applications in disease monitoring and personalized treatment strategies.

Проведено исследование электрофизических параметров плазмы, состава газовой фазы и кинетики реактивно-ионного травления кремния в смесях CF₄ + Ar/He и C₄F₈ + Ar/He с переменным содержанием инертных компонентов. При совместном использовании диагностики плазмы (зонды Лангмюра, оптическая эмиссионная спектроскопия) и моделирования кинетики плазмохимических процессов а) выявлены механизмы влияния соотношения Ar/He на концентрации активных частиц (атомов фтора, полимеробразующих радикалов и положительных ионов), формирующих брутто-результат взаимодействия плазмы с обрабатываемой поверхностью; б) разделены вклады физической и химической составляющих скорости травления; и в) проведен анализ механизма травления в приближении эффективной вероятности взаимодействия. Показано, что общими тенденциями при замещении аргона на гелий в обеих смесях являются снижение температуры и концентрации электронов, уменьшение степеней диссоциации многоатомных частиц, приводящее к аналогичному изменению концентраций менее насыщенных фторуглеродных радикалов и атомов фтора, а также снижение скорости травления кремния, обусловленное изменением кинетики гетерогенной реакции Si + xF → SiF_x. Изменение эффективной вероятности этой реакции с ростом доли гелия в смеси согласуется со снижением полимеризационной способности в смеси CF₄ + Ar/He, но противоречит росту полимеризационной способности в плазме C₄F₈ + Ar/He. Сделано предположение, что причиной последнего эффекта служит увеличение (по сравнению с величиной, определяемой концентрацией атомов фтора в плазме) потока атомов фтора на границе полимер/кремний. Причиной этого служит генерация атомов фтора в слое полимера увеличивающейся толщины за счет дефторирования под действием ионной бомбардировки. Для цитирования: Ефремов А.М., Бетелин В.Б., Kwon K.-H. Влияние соотношения Ar/He на состав плазмы и кинетику травления кремния в CF₄- и C₄F₈- содержащих трехкомпонентных смесях. Изв. вузов. Химия и хим. технология. 2025. Т. 68. Вып. 6. С. 41-51. DOI: 10.6060/ivkkt.20256806.7181.

проведен анализ и обобщение предпосылок, используемых для моделирования плазмы индукционного разряда в диапазоне условий, характерном для реакторов реактивно-ионного травления кремния и его соединений. Подтверждено, что применение функции Максвелла для энергетического распределения электронов обеспечивает корректное описание кинетики процессов под действием электронного удара. Показано, что реализация как прямого (основанного на решении уравнений химической кинетики с привлечением данных зондовой диагностики плазмы в качестве входных параметров), так и самосогласованного (дополненного уравнениями баланса вкладываемой мощности и скоростей процессов ионизации/рекомбинации заряженных частиц) алгоритма моделирования обеспечивает удовлетворительное согласие результатов расчета с данными независимых экспериментов. Приведены примеры сравнения расчета с экспериментом для плазмы Ar, Cl2 и CF4. Отмечено, что применение самосогласованного алгоритма в сложных многокомпонентных системах затруднено отсутствием или низкой достоверностью данных по сечениям процессов под действием электронного удара и транспортным характеристикам (коэффициентам диффузии, подвижностям) нестабильных продуктов плазмохимических реакций. we summarized and analyzed the assumptions used for simulating inductive discharge plasmas under typical reactive-ion etching conditions. We confirmed that applying the Maxwellian approximation to the electron energy distribution function provides an accurate description of the kinetics of electron impact processes. We demonstrated that both direct simulation (based on solving chemical kinetics equations with Langmuir probe diagnostics data as input) and self-consistent simulation (incorporating input power balance and ionization/recombination balance equations for charged particles) achieve satisfactory agreement with data from independent experiments. We provided examples comparing simulation predictions with experimental data for Ar, Cl2 and CF4 plasmas. However, the application of self-consistent simulation in complex multi-component systems is limited by the lack or low reliability of data on electron impact cross-sections and transport characteristics, such as diffusion coefficients and mobilities for unstable plasma chemical reaction products.

This work discusses the influence of inert carrier gases, Ar and He, on both gas-phase plasma characteristics and ZnO etching rate under typical reactive-ion etching conditions in the hydrogen bromide environment. Plasma diagnostics by Langmuir probes and 0-dimensional plasma modeling allowed one to compare how the content of given carrier gas does influence electrons-and ions-related plasma parameters, kinetics and densities of plasma active species. It was found that the transition toward Ar- or He-rich plasmas a) causes the growth of electron temperature (due to lower electron energy losses in collisions with atomic species); b) reduces plasma electronegativity; and c) results in opposite changes in both ion density and ion flux. The last phenomenon is due to opposite changes in total ionization rates determined by sufficient difference in ionization rate coefficients for Ar and He atoms. Important features of HBr + Ar plasma at 0–80% Ar are also the slower-than-linear fall of Br atom density (due to the intensification of electron impact dissociation for both HBr and Br2 molecules) as well as an increase in H atom density (due to decreasing their loss rate in gas-phase reactions). Etching experiments indicated that the ZnO etching rate is mostly contributed by the ion-assisted chemical reaction while the reaction rate decreases faster compare with the Br atom flux. The corresponding decrease in the effective reaction probability may be related to changes in both ion bombardment intensity and hydrogen passivation effect. For citation: Efremov A.M., Smirnov S.A., Betelin V.B., Kwon K.-H. Plasma parameters and reactive-ion etching kinetics of ZnO in hydrogen bromide: the influence of inert carrier gas. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2024. V. 67. N 12. P. 86-95. DOI: 10.6060/ivkkt.20246712.7081.

In this work, we investigated the influence of inert carrier gas on electro-physical plasma parameters, steady-state densities of active species and kinetics of their interaction with ZrO2 under the condition of “soft” reactive-ion etching in chlorine. This regime assumes the lower-than-usual negative bias voltage in order to reduce both ion bombardment energy and etched surface damage. The combination of plasma diagnostics by Langmuir probes and 0-dimensional plasma modeling allowed one to analyze formation and decay kinetics for neutral and charged species at various gas mixing ratios. It was found that the mixing of Cl2 with Ar or He at constant total gas pressure a) causes an increase in both electron temperature and plasma density; b) increases the Cl2 dissociation degree through the acceleration of electron-impact processes; and c) intensifies the ion bombardment by the change of ion flux. From etching experiments, it was found also that the ZrO2 etching rate is mostly composed by its chemical component, but does not correlate with the change in the Cl atom flux. The latter reveals that a) the dominant ZrO2 etching mechanism is the ion-assisted chemical reaction and b) an increase in the effective reaction probability toward Ar or He rich plasmas reflects the acceleration of ion-induced heterogeneous effects, such as the destruction of Zr-O bonds and/or the desorption of low-volatile ZrClx compounds. The lower neutral/charged ratio obtained in Ar-containing plasma allows one to assume the more anisotropic etching. It was shown that above findings are surely valid in the pressure range of 4–12 mTorr as well at bias powers of 100 – 300 W. For citation: Efremov A.M., Smirnov S.A., Betelin V.B., Kwon K.-H. Concerning effects of inert carrier gas on densities of active species and ZrO2 etching kinetics in chlorine plasma. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2024. V. 67. N 11. P. 40-54. DOI: 10.6060/ivkkt.20246711.7073.

The tasks of analyzing and visualizing the dynamics of a viscous incompressible fluid in conditions of complex flow geometry based on traditional grid and projection methods are associated with significant requirements for computer performance to achieve the set goals. To reduce the computational load in solving this class of problems, algorithms for constructing artificial neural networks (ANNs) can be used, using exact solutions of the Navier–Stokes equation system on a given set of spatial regions as training sets. An ANN is implemented to construct flows in areas that are complexes made up of training sets of standard axisymmetric regions (cylinders, balls, etc.). To reduce the amount of calculations in the case of 3-D problems, invariant flow manifolds with smaller dimensions are used. This allows you to identify the detailed structure of solutions. It is established that the typical invariant regions of such flows are rotation figures, in particular, homeomorphic torus, forming the structure of a topological bundle, for example, in a ball, a cylinder and in general complexes composed of such figures. The structures of the flows obtained by approximation by the simplest 3-D vortex unsteady flows are investigated. Classes of exact solutions of the Navier–Stokes system for an incompressible fluid in bounded regions of space based on the superposition of the above topological bundles are distinguished. Comparative computational experiments indicate a significant acceleration of computational work in the case of using the proposed class of ANNs, which allows the use of computing equipment with low performance.