Kirill Alekseevich Zykov

The stability of miRNAs in biological fluids and their association with pathological conditions position them as promising biomarkers for non-invasive cancer diagnostics, including those for non-small cell lung cancer (NSCLC). However, variability in miRNA expression and technical aspects of quantitative reverse transcription PCR (RT-qPCR) require effective normalization to accurately assess miRNA levels and identify biological differences. Despite the availability of multiple normalization methods, there is no consensus on the optimal approach for circulating miRNA data. This study provides a systematic methodological benchmarking of five normalization strategies—pairwise normalization, Tres normalization, Quadro normalization, normalization to the overall mean, and normalization to the exclusive mean—applied to RT-qPCR data of 17 miRNAs from plasma EVs of NSCLC patients and healthy donors. The aim was to evaluate their impact on the performance of machine learning models. For each normalization method, Random Forest models were built. Models were evaluated using accuracy, F1 score, AUC-ROC, AUPRC, precision, sensitivity, specificity, MCC, and overfitting gap. Pairwise normalization consistently outperformed all other methods across most metrics, achieving the highest AUC-ROC and AUPRC and the lowest overfitting gap, with statistically significant differences compared to other methods. Pairwise normalization offers a computationally simple, high-performing option for such benchmarking applications.

The aim of this pilot study was to assess the effect of salbutamol 400 µg on lung diffusing capacity (DLCO) and alveolar volume (VA) during bronchodilator test in patients with respiratory disorders, and to evaluate whether future studies with adequate statistical power are warranted. Materials and methods. A prospective longitudinal study was conducted in 51 adult patients (82% men, median age 44 years) with respiratory diseases. All patients underwent spirometry and DLCO measurement before and 15 minutes after inhalation of 400 µg of salbutamol. Results. No significant effect of salbutamol inhalation on mean DLCO values was observed ( p = 0.39), whereas a significant increase in VA was noted ( p = 0.03). Cohen’s d effect sizes were 0.026 and 0.056 for DLCO and VA, respectively, confirming the lack of a significant effect. In 10% of the patients, the DLCO change exceeded the test-retest repeatability threshold (±2 mL/min/mm Hg). The minimum sample size for future studies was 210 patients. Conclusion. Inhaled salbutamol (400 µg) has no clinically significant systemic effect on DLCO. The observation of individual variability in DLCO response in 10% of the patients supports the need for larger studies (n ≥ 210) to definitively assess the impact of β₂-agonists on gas exchange.

Acute respiratory distress syndrome (ARDS) is a common condition among intensive care unit patients and is associated with high mortality. Currently, there are no unified therapeutic strategies, including for the use of systemic glucocorticosteroid (GCS) therapy, in the management of ARDS of various etiologies. Using our previously developed non-surgical and reproducible model of unilateral total diffuse alveolar damage (ARDS/DAD) in the left lung of ICR mice, we investigated the effects of GCS with different durations of action and administration regimens on lung function recovery. Our data show that repeated-course administration of dexamethasone promoted complete normalization of respiratory function, as well as restoration of aeration and perfusion of the left lung in mice following ARDS/DAD induction. In contrast, a single administration of the same drug or the use of a prolonged-release formulation, despite exhibiting anti-inflammatory effects, did not provide adequate lung tissue recovery and, in some cases, even exacerbated injury. These results underscore that in ARDS therapy, not just the use but the specific dosing regimen of glucocorticoids is critically important for driving complete functional and structural lung repair.

BACKGROUND: Asymptomatic development and untimely diagnostics of lung cancer are the main reasons of high mortality caused by this disease. The development of tests based on “fluid biopsy”, which analyze circulating nucleic acids in blood, including the microRNA (miRNA) derived from the microvesicles, can be implemented as an effective screening test for lung cancer assuring the timely detection of the disease. AIM: To analyze the relative expression of 17 miRNAs in the microvesicles fraction from blood plasma samples from patients with non-small-cell lung cancer (NSCLC) and healthy donors. METHODS: The blood plasma microvesicles were isolated by aggregation-precipitation. miRNA was then isolated from the obtained blood microvesicles fraction using the glass fiber filters. Using the method of reverse transcription polymerаse chain reaction, an evaluation was carried out for the diagnostic efficiency of previously proposed miRNA pairs. This analysis was also used to select the most effective diagnostic pairs and panels. RESULTS: The obtained data have confirmed the diagnostic efficiency of four miRNA pairs (-31/-125b; -133b/-374a; -133b/-425; -133b/-222). The sensitivity and the specificity of distinguishing NSCLC patients from donors were 79% and 100%, respectively. Further analysis using paired normalization, compiling the regression models and multiple sample generations yielded three independent minimal panels of miRNA pairs, capable of diagnosing NSCLC with 100% accuracy: (1) -19b/-425, -125b/-378a, -205/-660; (2) -324/-374a, -30e/-92a, -125b/-378a; (3) -324/-374a, -125b/-378a, -205/-660. CONCLUSION: The diagnostic performance of the proposed miRNA panel across independent cohorts, along with the observed inter-cohort variability, supports its promising potential for NSCLC screening test development. These data demonstrate the necessity to identify additional multi-purpose miRNA markers and to validate the panel in further independent patient groups. Such research is essential to establish a reliable and timely miRNA-based screening tool for NSCLC.

Lung cancer (LC) remains a leading cause of global cancer mortality, driving the need for novel timely detection strategies, i.e., stages I–II detection when tumor curation is efficient. Circulating microRNA (miRNAs), with their unique stability in biofluids, offer a powerful approach for non-invasive detection. This review compiles validated miRNAs implicated in the early stages of non-small-cell lung cancer (NSCLC), elucidating their roles in key oncogenic pathways such as epithelial-mesenchymal transition (EMT), PI3K/AKT/mTOR, and JAK-STAT, which regulate proliferation, apoptosis, and metastasis. Furthermore, we critically evaluate developed miRNA panels with a specific focus on advanced quantification and normalization strategies, including exogenous spike-in controls and data-driven methods like pairwise normalization, to enhance diagnostic accuracy. Consequently, we identify and rank the most viable miRNA candidates according to key analytical and clinical metrics, providing a clear roadmap for translating these biomarkers into effective panels for the timely detection of NSCLC.

The stability of miRNAs in biological fluids and their association with pathological conditions make miRNAs promising biomarkers for non-invasive disease diagnostics, including non-small cell lung cancer (NSCLC). However, variability in miRNA expression and technical aspects of quantitative reverse transcription PCR (RT-qPCR) necessitate effective normalization methods to ensure accurate evaluation of miRNA levels and identification of biological differences. In this study, we performed a comparative analysis of several miRNA normalization approaches applied to extracellular vesicles isolated from plasma of NSCLC patients, including pairwise normalization, “Tres” and “Quadro” normalization strategies, normalization to the mean, and normalization considering miRNA functional groups. Method effectiveness was evaluated using quality metrics of diagnostic models. The most robust results were observed with normalization methods utilizing miRNA pairs, triplets, and quadruplets, which provided high accuracy, model stability, and minimal overfitting. In contrast, normalization to the general or exclusive mean and functional group-based normalization showed lower efficiency in terms of classification performance and feature selection stability. These findings highlight the critical importance of normalization strategy choice to improve the accuracy and interpretability of RT-qPCR-based diagnostic models, particularly in the development of biomarker panels for NSCLC diagnostics. Pairwise normalization, combining computational simplicity and high efficiency, appears optimal for practical applications.

Lung cancer represents a heterogeneous group of malignant neoplasms, among which two main forms can be distinguished — the non-small-cell and the small-cell lung cancer. These subtypes significantly differ by the histological, the molecular-genetic and the clinical characteristics, which defines the necessity of precise differential diagnostics for selecting the optimal treatment tactics. The review highlights the modern methods of diagnostics for the non-small-cell and the small-cell lung cancer, including the instrumental diagnostics, the histological and immunohistochemical examinations. Special attention was paid to the pros and cons of the promising non- and minimally invasive approaches, such as the analysis of circulating tumor cells, of the extracellular DNA, of the miRNA, of the marker proteins, of the volatile organic compounds and of the modern medical visualization (radiomics). Despite the significant progress in developing new diagnostic approaches, the problems remain that are related to the heterogeneity of tumors, the limited accessibility of the materials of small-cell lung cancer and the necessity of standardizing the new methods. The promising direction seems to the integration of multimodal approaches, combining the fluid biopsy, radiomics and the algorithms of machine learning, which can increase the precision of diagnostics and optimize the personalized treatment of the patients with various subtypes of lung cancer.

β-adrenoreceptor (ADRB) ligands are actively used in the therapy of bronchopulmonary and cardiovascular diseases. When using these drugs, it is important to assess changes in ADRB content in different tissues. In most cases, the direct measurement of ADRB content in lung and heart cells is not possible. ADRB2 content in peripheral blood lymphocytes (or mononuclear cells) was shown to correlate with that in myocardial cells. It has been suggested that blood lymphocytes can be used to monitor ADRB content in solid organs. However, the estimation of ADRB1 content in myocardium from its content in peripheral lymphocytes is not possible due to the low content of ADRB1 in lymphocytes. In the present study, we performed simultaneous determination of ADRB1 and ADRB2 both in the total population of PBMCs and in isolated subpopulations of monocytes, T-lymphocytes, and NK-cells from 23 healthy donors using the modified radioligand method. The highest amount of ADRB2 was detected in NK cells, followed by PBMCs, monocytes, and T cells. The content of these receptors in all blood cell subpopulations was significantly correlated with each other, suggesting the possibility of using PBMCs to monitor ADRB2 in solid organs. For the first time, ADRB1 was detected in monocytes and NK cells.

The aim of this study is to evaluate the effectiveness of the modified DCSI questionnaire (Dyspnea, Cough, Smoking, chronic recurrent respiratory Infections) developed by us to identify broncho-obstructive diseases (BOD) (COPD and bronchial asthma) in patients with cardiovascular diseases (CvD) and to compare the indicators of spirometric research in different groups of cardiac patients formed on its basis.Materials and methods. The sample consisted of patients over 18 years of age with arterial hypertension (AH), including chronic heart failure (CHF), coronary heart disease (CHD), heart rhythm disturbances (HRD), admitted to the National Medical Research Center of Cardiology over a two-year period. The sample consisted of 1000 cardiology patients, including 137 patients with comorbid COPD and bronchial asthma diagnosed before participation in the study, 71 patients with comorbid COPD and bronchial asthma diagnosed for the first time during the study, 792 cardiology patients without comorbid COPD and bronchial asthma. All cardiac patients filled out the modified DCSI questionnaire in the emergency room. All cardiac patients underwent pulmonary examination, which included computer spirometry (including bronchodilator test) in accordance with the recommendations of the European Respiratory Society. The main spirometric parameters were recorded: Gaensler index (modified Tiffeneau index, FEv1/FvC) (normal >70%), FEv1% (normal >80%) and FvC% (normal >80%). Patients with deviations detected in spirometry data were consulted by a pulmonologist.Results. All cardiac patients with COPD and bronchial asthma (137 patients with previously diagnosed comorbid COPD and bronchial asthma and 71 patients with newly diagnosed comorbid COPD and bronchial asthma during the study) had ≥2 points on the DCSI questionnaire. Cardiac patients without comorbid COPD and bronchial asthma had Conclusions. The DCSI questionnaire developed by us for screening risk factors and symptoms of broncho-obstructive pathology in patients admitted to a cardiology hospital effectively excludes comorbid COPD and bronchial asthma at <2 points (0-1) and identifies previously undiagnosed comorbid COPD and bronchial asthma at 4 points. At 2 or 3 points, the diagnosis of COPD and bronchial asthma is potentially probable, and routine computer spirometry is recommended for a cardiac patient. Cardiology patients with newly diagnosed comorbid COPD and bronchial asthma have lower spirometric parameters (FEv1%, FvC%, Gaensler index) than patients with previously diagnosed comorbid COPD and bronchial asthma.

Background/Objectives: Effective anti-inflammatory treatment for COVID-19 is necessary. It was shown that ultra-low doses (100-fold lower than therapeutic ones) of alkylating drug melphalan (MEL) interact with cytokine cell receptors without DNA damage. A method of treating severe COVID-19 with ultra-low doses of MEL inhalations was proposed. The objective was to study the efficacy and safety of MEL inhalations for COVID-19 pneumonia treatment. Methods: An open-label comparative study (NCT04380376) with 120 patients divided into two groups was conducted. The control group (CG) received standard treatment, and the melphalan group (MG) also received seven daily 0.1 mg MEL inhalations. Changes in clinical improvement, inflammatory markers, and CT lung scan data were primary and secondary endpoints. Results: Patients in the MG showed significantly better clinical outcomes compared to the CG, with improvements in dyspnea according to the WHO Ordinal Scale of Clinical Improvement and the modified Borg Scale, CT scans, and inflammatory markers. No adverse effects (including irritant and bronchoconstrictor effects) possibly related to MEL were reported. Conclusions: This study demonstrated the efficacy of incorporating ultra-low-dose MEL inhalations into the therapeutic regimen for patients with COVID-19-associated pneumonia. This conclusion is supported by a statistically significant improvement in clinical outcomes, as assessed by the OSCI, a more rapid reduction in the severity of dyspnea, and a marked anti-inflammatory effect, evidenced by a faster decline in C-reactive protein levels. No adverse effects were observed with the proposed treatment method. Further large-scale randomized clinical trials are warranted to validate these findings and to evaluate the potential for the implementation of ultra-low-dose MEL inhalation in clinical practice.