Current issue

Modern pharmaceutical science is undergoing signi­ficant changes due to the active integration of computer techno­logies into the drug development process. Prior to the conventional stages of synthesis and experimental testing, researchers are increasingly turning to in silico methods, which enable the simulation of the structure and pharmacological effects of chemical compounds with a high degree of predictive accuracy. This approach significantly saves time and financial resources, optimizing subsequent experimental studies. In parallel, there is an active development of epigenome-targeted therapy, a new approach that allows for the modulation of gene expression involved in pathological processes without directly altering the primary DNA structure. Using chelidonic acid as a case study, we present a pipeline for computer-based assessment of small molecule effects on gene expression and metabolic pathways. The algorithm is based on the use of the DIGEP-Pred 2.0 web service, followed by multilevel bioinformatics analysis, inclu­ding: (1) gene over-representation analysis; (2) assessing the involvement of metabolic pathways; (3) functional clustering of pathways. The proposed approach can help solve problems in both fundamental and applied research on the molecular mechanisms of drug action.

The development of novel approaches to induce apoptosis in tumour cells remains a key challenge in contemporary biomedicine. Given the exceptional thermal conductivity of graphene, we employed one of its deriva­tives — graphene oxide (GO) — to achieve localised heating of cells under near-infrared (NIR) irradiation in vitro. In this study, graphene oxide nanoparticles coated with either linear (LP-GOs, Ø184 ± 73 nm) or branched (BP-GOb, Ø1376 ± 48 nm) polyethylene glycol were used. The MCF-7 breast adenocarcinoma cell line served as the cancer model. Cells were cultured for 24 hours to allow monolayer formation, after which LP-GOs and BP-GOb nanoparticles were added at final concentrations of 5 and 25 μg/mL. The cells were then irradiated with NIR light using a Hydrosun-750 lamp for 1 hour. Cell viability, nanoparticle sorption / uptake and the rates of early and late apoptosis / necrosis were assessed at 1 and 24 hours post-irradiation.

MCF-7 cells exhibited the capacity for sorption of PEGylated graphene oxide nanoparticles, including under conditions of NIR irradiation. After 24 hours of incubation, the proportion of PC7+ (GO-positive) cells reached approximately 10 % at a concentration of 5 μg/mL and 50 % at 25 μg/mL. NIR-irradiated nanoparticles did not produce statistically significant changes in cell viability or apoptosis/necrosis rates. However, a trend towards increased cell death and apoptosis was observed 24 hours post-irradiation.

Periprosthetic joint infection (PJI) is a serious complication of large joint arthoplasty, often necessitating repeated surgical interventions and prolonged antimicrobial therapy. Polymerase chain reaction (PCR) offers significant advantages in the aetiological diagnosis of PJI, namely rapid result acquisition and high sensitivity and specificity. This study aims to use real-time PCR to determine the role of Staphylococcus spp., Streptococcus spp., and Enterobacteriaceae as microbial aetiological agents of PJI, and to examine their presence in the biocenoses of the upper respiratory, urogenital, and gastrointestinal tracts in patients with PJI, in order to assess the potential role of opportunistic bacteria as endogenous risk factors for infection follo­wing large joint arthroplasty.

The findings confirm that the detection of Staphylococcus spp., Streptococcus spp. and Enterobacteriaceae DNA in synovial
fluid and synovial membrane fragments in patients with clinical signs of infection serves as a microbiological indicator of PJI. Furthermore, the microbial composition of the upper respiratory, urogenital and gastrointestinal biocenoses is analysed. A diagnostically significant criterion for identifying patients at risk of PJI is the detection of opportunistic microorganism DNA at concentrations of ≥1.0 × 10⁴ copies/ml in the study biotope, accompanied by clinical evidence of local inflammation.

This manuscript is dedicated to the concept of emergence in modern systems biology and discusses the essence of this concept, its role, and its implementation using the example of epidemic modeling for COVID-19, where three dimensions of emergence should be integrated: (i) the emergence of the epidemic and the spread of the virus in a population from interactions between susceptible, infected, and recovered individuals; (ii) the emergence of health-related properties of one individual from interactions between biomolecules; (iii) the emergence of the research project from interactions between various institutions collecting different pieces of clinical data.

Systems biological understanding of biological emergence may require changes in data management approaches. By adding the concept of Emergence, classical FAIR data management may be extended to FAIRE, where data become not only Findable, Accessible, Interoperable, and Reusable, but also Emergeable (FAIRE). To implement FAIRE data management, we propose a Silicon Organism Model-Engrossed Data Integration approach (SOMEDAI), where data are not just stored in separate databases, but are integrated into a mathematical model. The latter allows for validating data consistency and using the data to reconstruct the emergent behaviour of the whole system.

Post-COVID syndrome, affecting up to 48 % of patients after COVID-19, is characterized by persistent immune dysregulation, including innate immunity dysfunction and increased susceptibility to reactivation of chronic infections. Cytomegalovirus (CMV), which persists in 60—90 % of the population, can cause severe complications under immunosuppressive conditions, such as hepatitis, encephalitis, and multiorgan failure. The relevance of this study lies in investigating the relationship between CMV reactivation and the immunopathogenesis of post-COVID syndrome, particularly in the context of neutrophil dysfunction and complement system impairment. The aim of this study was to evaluate the features of neutrophil phagocytic activity and complement system activity in patients with post-COVID syndrome and concurrent CMV infection.

Methods included assessment of neutrophil phagocytic function using 1.7 μm latex particles: counting phagocytic cells per 100 neutrophils, calculating the phagocytic index, phagocytic number, and phagocytic intensity via light microscopy. Neutrophil bactericidal activity was analyzed using the standard nitroblue tetrazolium (NBT) test. Complement system component levels were measured by enzyme-linked immunosorbent assay (ELISA).

The findings will help identify specific impairments in phagocy­tic function and complement-mediated immunity associated with CMV reactivation in post-COVID syndrome. The results of this study may provide a basis for developing personalized immunomodulatory approaches for this patient population.

Background. The pathogenesis of ischemic cardiomyopathy (ICM) is not fully understood.

Aim. This study aims to identify key pathogenetic factors involved in the development of ICMP through multifactorial analysis and to determine the extent of their contribution to disease progression.

Material and methods. The study included 60 patients with coronary heart disease (CHD) and ICMP, and 44 patients with CHD without evidence of cardiomyopathy.Blood and bone marrow samples were analysed by flow cytometry to assess the content of desquamated endothelial cells (DEC); classical, intermediate, non-classical, transitional monocytes; and early and late endothelial progenitor cells (EPC). In plasma and bone marrow supernatant, the concentrations of VEGF-A, SDF-1, MCP-1, M-CSF, GM-CSF, TNF-α, HIF-1α, IL-6, IL-10, IL-13, and IFN-γ were assessed using immunofluorescence and enzyme-linked immunosorbent assay. Correlation and multivariate factor analysis were performed at p < 0.05.

Results. At the blood level, the primary factor terms of influence on ICMP was the concentrations of SDF-1, HIF-1α, M-CSF and DEC, accounting for 41.8% of the total variance. The second most influential factor was the concentration of IL-10 and MCP-1 (31.1%); the third was the content of late endothelial progenitor cells (EPCs) (26.3%); and the fourth, the levels of IL-6 and IL-13 (21.6%). In the bone marrow, the most significant factor was the concentrations of IL-10, IFN-γ, IL-13, M-CSF/IL-13, and classical monocytes (47.1%). The second factor involved non-classical monocytes and TNF-α (35.2%); the third, VEGF-A, MCP-1, GM-CSF, and HIF-1α (32.7%); and the fourth, early EPC and IL-6 (25.5%). In the bone marrow of patients with CHD without cardiomyopathy, a significant negative correlation was observed between IL-6 and SDF-1 concentrations (r = – 0.781, p = 0.013), while in patients with ICMP, a strong positive correlation was found between IL-6 and MCP-1 (r = 0.899, p = 0.014).

Conclusions. Pathogenetic factors contributing to the development of ICMP were identified. In the blood, the most significant was an anergic mediator response of HIF-1α and SDF-1 to hypoxia with hyperproduction of IL-10. In the bone marrow, deficiency of classical monocytes and the ratio of M-CSF/IL-13 under conditions of excess IFN-γ.