University of Economics and Innovation

Toll-like receptors (TLRs) play a significant role in the tumor microenvironment, including in brain tumors, as their activation can both support an anti-tumor response and promote tumor progression through chronic inflammation. However, the precise mechanisms of TLR action have not been fully elucidated, likely due to their complex role in both innate and adaptive immunity. The aim of this study was to analyze serum TLR2 and TLR9 concentrations in patients with glioma in the context of potential Epstein–Barr virus (EBV) infection. TLR9 levels were also analyzed in relation to the presence of viral DNA and EBER molecules in tumor tissue, as well as EBV-related serological responses. The results demonstrate that TLR2 and TLR9 levels were higher in patients with glioblastoma than in control groups. Notably, however, lower TLR9 concentrations were observed in patients testing positive for EBV. Furthermore, a detailed data analysis revealed a link between TLR9 levels and the presence of EBER molecules and/or EBV DNA in tumor tissue. Nevertheless, given the undefined role of EBV in the pathogenesis of glioblastoma, further intensive research in this area is required.

The functioning of an organization can be assessed using quality attributes such as availability, performance, integrity, security, and digital sovereignty. The digital sovereignty is a relatively new quality attribute, and it requires dedicated analysis and scientific research, particularly in the context of data centers. At present, there is a lack of standards and systematic methods for maintaining and assessing digital sovereignty, whereas digital security has been extensively studied and standardized. Since security and digital sovereignty are highly correlated, it is legitimate to base solutions enhancing digital sovereignty on present security standards. This paper suggests an approach towards assessing the digital sovereignty of data centers through some combination of metrics, risk analysis, and holistic enterprise architecture models. This method allows for an assessment of the present state of sovereignty and a projection of possible loss of sovereignty using risk management techniques. Enterprise architecture models, developed using the ArchiMate graphical language, are used to describe the structure of data centers and to inventory organizational assets subject to digital sovereignty requirements. The proposed reference models provide a clear and systematic representation of data centers, supporting the identification of critical assets and architectural solutions necessary to ensure and assess digital sovereignty.

Recent research suggests a link between EBV and brain cancer, especially in high-grade gliomas, but its role has not been sufficiently elucidated. Therefore, we evaluated its occurrence in brain cancer. For this purpose, the EBV DNA and LMP-1 in tumor tissue, the level of viral load in the cerebrospinal fluid (CSF), and the serological status of patients were analyzed. We detected EBV DNA in 28.9% (42/145) of glioma samples, among which 28 were isolated from glioblastomas (GBs) and 14 from other gliomas. LMP-1 was detected in 26 (92.8%) GB samples and 5 (35.7%) samples from other gliomas. The EBV DNA load in the CSF was significantly higher in GB compared to other gliomas; anti-EBNA1, anti-EBVCA, anti-EA, and anti-Zta antibodies were detected in the serum of GB patients; and their concentration was higher in GB patients. Further research is needed to determine whether and to what extent EBV contributes to glioma development. Elucidating the role of latent EBV genes synthesized in glioblastoma is important for understanding the role of viral infection in cancer development and progression in this hitherto poorly studied area.

This study draws on the experience of selected European micro-regions in Germany, Poland, and Romania, representing different stages of a just transition, to identify applicable strategies for the Ukrainian context. The research aims to assess the spatial and economic preconditions for transformation, compare them across regions, and propose adaptation pathways. Methodologically, it combines spatial–economic analysis, comparative assessment, and critical evaluation of EU strategic approaches. The results reveal substantial disparities: European coal regions generally benefit from high population density, diversified economies dominated by the tertiary sector, strong research and education infrastructure, and cross-border advantages. In contrast, Ukrainian micro-regions are marked by demographic decline, low population density, rural settlement patterns, and complex security conditions. Based on these findings, the study recommends a localized transformation model emphasizing targeted investments, the strategic use of cross-border location, and the repurposing of existing specialized logistics and production infrastructure for new economic activities. The proposed approach contributes to the discourse on just transition by aligning regional development strategies with local structural capacities and constraints. The results obtained may be applicable in other European countries.

Introduction: The study aimed to evaluate the effectiveness of the zoomorphic robot Brian in the therapy of children diagnosed with autism spectrum disorder (ASD) compared to standard therapist-led interventions. The assessment focused on the child's level of interest in the robot, willingness to respond to verbal commands given by the robot, adaptive behaviors, social communication, imitation during play, and recognition of emotional states presented by the robot. Materials and methods: The study included fourteen children, with a total of 116 therapy sessions conducted. Each child participated in four sessions with the zoomorphic robot and four sessions with a therapist. During the sessions, the children's responses to verbal commands, ability to recognize emotions, and skills in social communication and imitation were evaluated. Results: The study showed a significantly greater willingness of autistic children to respond to verbal commands given by the robot than to the same commands spoken by the therapist. Additionally, children with ASD demonstrated better recognition and naming of emotional states displayed on the robot’s face compared to those on a human face. Conclusions: In interaction with the robot, autistic children acquired and exhibited desired social communication and imitation behaviors more quickly than in traditional therapy conducted by a therapist. These results suggest that robots may serve as an effective tool to support the therapy of children with ASD. Keywords: robot-assisted therapy, human-robot interaction, social robots, autism spectrum disorder