Background/Objectives: Syncope is a common clinical problem often requiring pharmacological treatment, yet evidence-based therapies remain limited. Midodrine, a vasopressor agent, is frequently used, though its autonomic effects over time remain unclear. This study aimed to assess autonomic nervous system changes and blood pressure response in syncope patients treated with Midodrine, placebo, or their combination. Additionally, the structural properties of the Midodrine placebo were analyzed using nanotechnological methods. Methods: A total of 67 patients with syncope were randomized to receive Midodrine, sucrose placebo, or their combination over three weeks. All participants underwent 24 h Holter ECG with heart rate variability (HRV) analysis and ambulatory blood pressure monitoring before and after therapy. Structural analysis of Midodrine tablets, sucrose, and Midodrine placebo was performed using Raman spectroscopy and X-ray diffraction (XRD). Results: Patients receiving the Midodrine–placebo combination showed a significant reduction in HRV markers of parasympathetic activity (RMSSD, pNN50, HF) and an increase in sympathetic dominance (LF/HF ratio) compared to the other groups. Only this group showed a statistically significant rise in average systolic and diastolic blood pressure. Raman and XRD analyses revealed structural alterations in the sucrose-based placebo compared to its original form, indicating subtle changes in crystalline structure. Conclusions: In this exploratory study, the combination of Midodrine and placebo was associated with autonomic imbalance and modest increases in blood pressure, which may indicate a potential effect in patients with hypotensive syncope phenotypes. These preliminary findings should be interpreted with caution, and the structural modifications observed in the placebo formulation are presented as hypotheses requiring further investigation rather than established mechanisms.

Diffusion-triggered convection can occur in a gravitationally stable system of two superimposed mixtures. As instability develops, two distinct patterns may emerge: double-diffusive (DD) or diffusion-layer convection (DLC). Traditionally, nonsymmetric patterns above and below the interface were thought to require chemical reaction. We show that symmetry can be broken by composition-dependent diffusion, with or without cross diffusion. Furthermore, only the composition-dependent cross diffusion can lead to a range of coexisting patterns and provide new insights into staircase instability.

A Boolean-algebraic framework for maximal-degree U-k-seminets is presented, unifying combinatorial and algebraic properties. This work extends Aczel’s quasigroup theory and Belousov’s k-net constructions by introducing a computational framework for U-k-seminets of maximal degree µ. Key results include: (1) explicit bounds for µ in terms of set cardinality t and t-order d (µ = t−d+2), (2) existence conditions for nonequipotent sets, and (3) inequalities governing µ and t ((t+2)/2 < µ ≤ t). Theorems are validated via tabulated solutions for m = t−d, demonstrating scalable applications in finite geometry and network design. The framework bridges partial quasigroups and block designs, offering algorithmic tools for seminets with maximal degree constraints.

Abstract Despite striking successes in identifying novel biomarkers for improved patient stratification and predicting disease progression, numerous challenges remain in the effective integration and exploitation of multiomic data in biomedical applications beyond cancer, for which most bioinformatics strategies are developed and validated. That focus on cancer severely limits the effective development and advancement of algorithms in machine learning and artificial intelligence that do not suffer degraded out-of-domain performance. Generalizability and interpretability of models, however, are also required for robust insights that may translate into clinical practice. Work across different independent datasets is critical for establishing models robust towards unwanted variation in assays, protocols, and cohort populations. Disease-specific context like ethnicity, socioeconomic background, sex, lifestyle, disease phase, and tissue type also strongly affect molecular profiles. We here discuss atherosclerotic cardiovascular disease (ASCVD) as a high-impact non-cancer use case for the challenges remaining in the development and application of the latest bioinformatics approaches to multiomics data integration. ASCVD remains the leading cause of death globally. Disease aetiology, progression, and therapy outcome depend on a complex interplay of genetic, environmental, and lifestyle factors. Integrating these diverse data types effectively remains a challenge but holds transformative potential for personalized medicine. Discovery and access to data of sufficient diversity and extent form key bottlenecks. We here compile a first comprehensive overview of key data sets in ASCVD to complement the established cancer-focused resources as a foundation for future effective development and application of state-of-the-art bioinformatics tools for multiomic data integration.

ABSTRACT Increasing oxygen transport through elevated hemoglobin concentration and red blood cell mass is a key objective of blood doping, commonly achieved via recombinant human erythropoietin (rHuEPO) administration or blood transfusions. While the Athlete Biological Passport (ABP) offers an effective indirect tool for detecting such manipulations, its sensitivity and specificity may be limited, particularly in cases involving microdoses or confounding physiological factors. To address these limitations, the identification of novel biomarkers that complement current ABP markers is essential. This study presents a targeted metabolomics approach to discover candidate biomarkers of rHuEPO administration by analyzing polar metabolites in plasma and serum from two administration studies: one involving a single CERA injection, and the other using multiple doses of epoetin delta. Hydrophilic interaction chromatography hyphenated with tandem mass spectrometry enabled the selective and sensitive detection of a panel of polar endogenous metabolites. Following data normalization and stringent quality control, generalized least squares models were applied to evidence temporal changes in metabolite signals. Among the most responsive and concordant markers across both studies were hypoxanthine and inosine, which showed significant and marked increases following rHuEPO administration. Notably, the relative increase of these metabolites coincided with the maximum in reticulocyte percentages, reflecting maximal erythropoietic activity. As intermediates in purine metabolism, their increases are likely tied to augmented purine turnover during red blood cell production. These findings suggest that hypoxanthine and inosine are promising candidate biomarkers to complement existing ABP parameters. However, further validation is required to confirm their reliability and applicability within the ABP framework.

This article questions the extraterritorial scope of the Digital Markets Act (DMA) in relation to the Western Balkans. We argue that the complex interplay between the requirement to adopt the DMA as part of the European Union (EU) accession process and the region’s limited capacity to enforce it may harm competition and consumer welfare. Moreover, it could diminish the EU’s appeal in the region. Given the potential lack of beneficial effects even after formal adoption, countries in the Western Balkans may turn to alternative regulatory models for digital market competition. These developments raise concerns about the effectiveness of the EU’s digital regulatory agenda beyond its borders. In response, we propose that the EU reassess the DMA’s extraterritorial reach to support better adoption and enforcement in the Western Balkans. A more tailored approach could help ensure that the DMA achieves its goals without producing unintended negative consequences in candidate countries.

CNS infections represent a unique challenge to clinicians due to significant morbidity and mortality. The role of ferritin as a reactant of various pathological conditions is currently being intensively investigated. The pathogenesis of cognitive impairment after acute neuroinfectious disease is not yet fully understood. It is believed to be a direct consequence of neuronal damage by the infection, but also by the activation of immunocompetent brain cells, with consequent disruption of signal conduction in a varying period of time after the infection has resolved. The aim of the study is to examine the prediction of ferritin on the degree of cognitive impairment in patients who have suffered from a CNS infection. The values of CSF ferritin were evaluated in three analyzed groups of subjects (bacterial, viral and group with normal CSF findings - meningism). The analyzed clinical data were correlated with the degree of neurocognitive impairment, and the relationship between CSF ferritin and the degree of cognitive impairment was analyzed. The conducted research is a retrospective-prospective analytical and clinical study that was conducted in the period from 01.01.2017 to 01.01.2020. The research includes 90 patients according to previously nominated criteria, divided into three groups, two “examined” and one “control”. The assessment of the cognitive status of the subjects was performed using the MMSE test. The SPSS for Windows software package (version 20.0, SPSS INC, Chicago, Illinois, USA) was used for statistical analysis of the obtained data. We confirmed that the CSF protein ferritin is a good predictor of distinguishing purulent from viral meningitis / meningoencephalitis. The obtained results did not confirm the hypothesis that elevated CSF ferritin values have a negative impact on cognition. Impairment of individual domains of cognition measured by MMSE I, such as “attention”, “calculation” and “memory” are more pronounced in purulent CNS infections. Impairment of individual domain MMSE II “calculation” is more pronounced in the purulent CNS infection category