The scarcity of high-quality wood encouraged the development of various technological processes for joining wood. The finger joint is one of the most widespread technological processes for wood joining. This study aimed to determine the effect of steaming and heat modification of beech wood, as well as the type of adhesive, on the mechanical characteristics of finger joints. Samples made from un-modified beech, steamed-treated, and heat-treated beech wood were bonded with polyvinyl acetate (PVAC), non-structural, and structural polyurethane (PUR) adhesives. Compressive tests on wood materials were used to evaluate their mechanical performance. The finger joint samples were tested for their bending performance. Modulus of rupture, modulus of elasticity, and compressive strength were calculated. An analysis of variance (ANOVA) was conducted to evaluate the impact of wood modification type and adhesive used on the mechanical characteristics of the finger joints. According to the results of this study, it can be concluded that the steaming process does not influence changes in the mechanical characteristics of the finger joints. Heat treatment of beech and the type of adhesive used significantly influence the tested mechanical characteristics of the finger joints and beech wood. Heat-treated beech had lower values of modulus of rupture (70 MPa) and density (690 kg/m3) and higher values of compression strength (59 MPa) in relation to un-modified (780 kg/m3) and steamed-treated (800 kg/m3) beech wood.

Background/Objectives: In many low- and middle-income countries (LMICs), including Bosnia and Herzegovina, oncology services are constrained by a limited number of specialists and uneven access to evidence-based care. Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT, may provide clinical decision support to help standardize treatment and assist clinicians where oncology expertise is scarce. This study aimed to evaluate the concordance, safety, and clinical appropriateness of ChatGPT-generated treatment recommendations compared to decisions made by a multidisciplinary team (MDT) in the management of newly diagnosed breast cancer patients. Methods: This retrospective study included 91 patients with newly diagnosed, treatment-naïve breast cancer, presented to an MDT in Bosnia and Herzegovina in 2023. Patient data were entered into ChatGPT-4.0 to generate treatment recommendations. Four board-certified oncologists, two internal and two external, evaluated ChatGPT’s suggestions against MDT decisions using a 4-point Likert scale. Agreement was analyzed using descriptive statistics, Cronbach’s alpha, and Fleiss’ kappa. Results: The mean agreement score between ChatGPT and MDT decisions was 3.31 (SD = 0.10), with high consistency across oncologist ratings (Cronbach’s alpha = 0.86). Fleiss’ kappa indicated moderate inter-rater reliability (κ = 0.31, p < 0.001). Higher agreement was observed in patients with hormone receptor-negative tumors and those treated with standard chemotherapy regimens. Lower agreement occurred in cases requiring individualized decisions, such as low-grade tumors or uncertain indications for surgery or endocrine therapy. Conclusions: ChatGPT showed high concordance with MDT treatment plans, especially in standardized clinical scenarios. In resource-limited settings, AI tools may support oncology decision-making and help bridge gaps in clinical expertise. However, careful validation and expert oversight remain essential for safe and effective use in practice.

Objectives This study aimed to investigate the associations between body mass index (BMI), physical activity levels (PALs) and sociodemographic factors (gender, age, education and marital status) with different outcomes (symptoms) of osteoarthritis (OA) severity, in patients with knee OA. Design Cross-sectional study. Participants The sample included 200 participants from southern Bosnia and Herzegovina (61 males, 65.1±9.01 years of age) who had been diagnosed with primary knee OA. Outcome measures OA symptoms as evidenced by the Western Ontario and McMaster Universities OA Index (WOMAC) scale, including three subscores (WOMAC-pain, WOMAC-stiffness, WOMAC-functionality) and total WOMAC score. The predictors included age (in years), gender (male or female), BMI, PAL, education level, urban/rural living environment and marital status (partnership). Results Female gender was correlated with the WOMAC-pain, WOMAC-stiffness and WOMAC-total. Older age was correlated with the WOMAC-pain and WOMAC-total. Patients who were better educated and reported higher PAL had better WOMAC functionality. BMI was the most significant factor of influence, with higher WOMAC-pain (OR 1.44, 95% CI 1.27 to 1.65), WOMAC-stiffness (OR 1.20, 95% CI 1.1 to −1.33), WOMAC-functionality (OR 1.26, 95% CI 1.13 to 1.40) and WOMAC-total (OR 1.29, 95% CI 1.6 to −1.44) scores in patients with higher BMI. Conclusions Results indicate the necessity of controlling body weight in patients with diagnosed knee OA irrespective of gender. Further prospective studies are warranted in order to establish causality between variables.

Abstract Introduction. Physical literacy (PL) and health literacy (HL) are important concepts that are theoretically associated with physical activity (PA), but studies have rarely examined these problems simultaneously in older adults, particularly women. The aim of this study was to evaluate the associations between HL and PL with PA in women older than 60 years from Croatia. Material and methods. The participants were 49 women from an urban center in southern Croatia who were tested on HL (via the validated Croatian version of the European Health Literacy Survey Questionnaire), PL (via the Perceived Physical Literacy Questionnaire for South Eastern Europe), and PA (via the Nordic Physical Activity Questionnaire – short version) in controlled settings. Different facets of PL and HL were univariately and multivariately correlated with weekly moderate-to-vigorous PA (MVPA) and weekly vigorous PA (VPA). Results. Almost 39% of the participants reached the World Health Organization recommendations for weekly PA. The PL variables were not significantly correlated with MVPA, nor with VPA (up to 6% of the common variance). The HL was significantly (p < 0.05) correlated with VPA across several subdomains (9% to 20% of the common variance). Multiple regression analysis revealed a significant multivariate association between HL subdomains and VPA (27% of the explained variance), indicating a positive influence of the higher HL on PA in older women. Conclusions. Promoting HL in older women can enhance PA by improving their understanding of the health risks and benefits of PA. Educational efforts should focus not only on providing information but also on helping women interpret and apply it in meaningful, everyday contexts.

Introduction: It is suggested that bladder cancer (BC) development is linked to glutathione S-transferase (GST) enzymes. This study aimed to determine the correlation between glutathione S-transferase Mu 1 (GSTM1), glutathione S-transferase Theta 1 (GSTT1), and N-acetyltransferase 2 (NAT2) variants with BC progression and recurrence rating. Materials and methods: This study included 105 Bosnian and Herzegovinian subjects: 60 patients with histopathologically confirmed BC and 45 controls without urological diseases. GSTM1, GSTT1 (rs36631 and rs17856199, respectively), and NAT2 (rs1799929, rs1799930, and rs1799931) were investigated. Results: Both one- and five-year probabilities of progression were not significantly different in GSTM1 and NAT2 polymorphisms. One-year probability of progression was significantly higher in the GSTT1 T-- (null) than the T++ (wildtype) genotype (14.7% (±6.9) vs. 8.9% (±6.7), respectively; p=0.048). Five-year probability of progression was significantly higher in the GSTT1 T-- than the T++ genotype (39.4% (±14.7) vs. 25.5% (±16.6), respectively; p=0.045). THE GSTT1 T-- genotype was an independent predictor in the one-year probability of recurrence and progression (p=0.03 and p=0.01, respectively). GSTT1 T-- genotype and age were independent predictors for the five-year probability of recurrence (p=0.032 and p=0.04, respectively) as well as independent predictors of the five-year probability of progression (p=0.012 and p=0.03, respectively). Conclusions: The GSTT1 T-- genotype was an independent predictor in the one- and five-year probabilities of both recurrence and progression of BC. GSTT1 rs17856199 may be a significant factor in the development of tumors and the course of disease in Bosnian and Herzegovinian BC patients.

Acute mesenteric ischemia (AMI) is a life-threatening condition characterised by oxidative stress, inflammation, apoptosis, and necrosis of intestinal epithelial cells. Different drugs with vasoactive, antioxidant, and anti-inflammatory properties have been used to treat AMI. Levosimendan is a drug with proven anti-ischemic effects used in the management of acute congestive heart failure. This study evaluated the protective effects of levosimendan pretreatment on intestinal, as well as lung, heart, and kidney tissue in a rat model of mesenteric artery ischemia/reperfusion (I/R) injury. Male Wistar rats (N = 24) were divided into four groups: control, I/R, levosimendan (LS) 1 mg/kg i.p, and LS + I/R (1 mg/kg i.p. 30 min before injury). I/R by itself caused elevation of oxidative markers (thyobarbituric acid reactive species (TBARS), hydrogen peroxide (H2O2), super oxide anjon radical (O2−), and nitrogen dioxide (NO2−)), induced inflammation (macrophage infiltration and Interleukin-6 (IL-6) production), and apoptosis (nuclear factor kappa light-chain enhancer of activated B cells (NF-κB), cleaved caspase-3 (CC3), and terminal deoxy-nucleotidyl transferase (TdT)-mediated dUTP nick end labelling (TUNEL)). Levosimendan pretreatment significantly reduced oxidative stress markers and enhanced antioxidant defences (catalase (CAT), reduced glutathione (GSH), and superoxide dismutase (SOD)). Histological analysis revealed reduced mucosal damage and preserved goblet cells in intestinal tissue. Similar protective effects of levosimendan were observed in other organs such as lung, heart, and kidney. Immunohistochemistry showed reduced epithelial apoptosis and upregulation of antioxidant and anti-inflammatory proteins. These findings highlight levosimendan’s ability to protect mesenteric I/R tissue injury and multi-organ damage by suppressing oxidative stress, inflammation, and apoptosis, emphasising its therapeutic potential in clinical settings.

Background/Objectives: Renal failure (RF) and systolic heart failure (sHF) are very often associated with each other, and their synergistic influence can affect the prognosis of acute pulmonary embolism (aPE) patients. The aim of this study is to evaluate the associations between RF, sHF, and in-hospital mortality in patients with normotensive aPE. Methods: We analyzed data from the Regional PE Registry (REPER), and 1968 patients with CT pulmonary angiography-confirmed aPE who had a systolic blood pressure of 100 mmHg and higher, and for whom creatinine blood levels and left ventricular ejection fraction (LVEF) were measured at admission to hospital were enrolled. The patients were divided into four groups: the first group comprised patients without renal and systolic heart failure, the second those with RF (creatinine clearance less than 60 mL/min), the third those with sHF (LVEF less than 50%), and the fourth those with both RF and sHF. The primary endpoint of this study was in-hospital all-cause mortality. Results: There are significant differences between in-hospital mortality among the groups: 38/1247 (3.0%) vs. 63/514 (12.9%) vs. 10/99 (10.1%) vs. 20/108 (18.5%) (p < 0.001). In the multivariable regression model adjusted for age, right ventricular dysfunction, and troponin levels, the presence of renal failure, sHF, and both were independently associated with in-hospital all-cause mortality with ORs of 3.59 (95%CI 2.04–6.30, p < 0.001) vs. 3.97 (1.71–9.25, p = 0.001) vs. 6.39 (3.15–12.99, p < 0.001), respectively. Conclusions: The association of renal failure and systolic heart failure has a deleterious prognosis in patients with normotensive aPE.

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

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.

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.

OBJECTIVE Previous studies have demonstrated that the speech reception threshold (SRT) can be estimated using scalp electroencephalography (EEG), referred to as SRTneuro. The present study assesses the feasibility of using ear-EEG, which allows for discreet measurement of neural activity from in and around the ear, to estimate the SRTneuro. Approach: Twenty young normal-hearing participants listened to audiobook excerpts at varying signal-to-noise ratios (SNRs) whilst wearing a 66-channel EEG cap and 12 ear-EEG electrodes. A linear decoder was trained on different electrode configurations to estimate the envelope of the audio excerpts from the EEG recordings. The reconstruction accuracy was determined by calculating the Pearson's correlation between the actual and the estimated envelope. A sigmoid function was then fitted to the reconstruction-accuracy-vs-SNR data points, with the midpoint of the sigmoid serving as the SRTneuro estimate for each participant. Main results: Using only in-ear electrodes , the estimated SRTneuro was within 3 dB of the behaviorally measured SRT (SRTbeh) for 6 out of 20 participants (30%). With electrodes placed both in and around the ear, the SRTneuro was within 3 dB of the SRTbeh for 19 out of 20 participants (95%) and thus on par with the reference estimate obtained from full-scalp EEG. Using only electrodes in and around the ear from the right side of the head, the SRTneuro remained within 3 dB of the SRTbeh for 19 out of 20 participants. .