Evaluating the somatic cell count (SCC) at the level of the herd or individual cows allows for efficient monitoring of mammary gland health. By analysing SCC, it is possible to identify subclinical cases of mastitis that do not manifest through visible clinical signs on the udder or changes in milk. This study was conducted on a modern dairy farm of the Holstein-Friesian breed in the municipality of Čapljina, Bosnia and Herzegovina. The total number of cows included in the study during 2022 and 2023 ranged between 325 and 335. Milk samples were preserved with azidiol and transported to the laboratory. Milk quality was assessed by determining the SCC in milk using the Fluoro-opto-electronic method, and by analysing the fat, protein, and lactose contents. The devices used in the study were CombiFoss 6200 – MilkoScan FT and Fossomatic FC 6000. A strong positive correlation was found between SCC and milk proteins, but not with milk fat. A significant negative correlation was found between SCC and lactose. There was no significant difference in the number of somatic cells by year, although there was a significant difference by season within the studied years. Winter stands out as the season with the lowest SCC, followed by spring and summer, while autumn had the highest count. Autumn also showed the largest oscillations in SCC, while spring had the smallest. Somatic cell counts over 200,000/mL were recorded from July to December 2022 and from May to November 2023. Zoohygiene conditions and milking hygiene measures should be additionally adjusted in summer and autumn to maintain the desired standards achieved in winter and spring.

Five neutral heteroleptic mononuclear vanadium(IV) hydrazone complexes ([VOL(bpy)]), derived from 2-hydroxy-5-methylacetophenone and various acid hydrazides (furoic, thiophene, benzoic, nicotinic, and isoniazid), were synthesized and shown to exhibit improved antidiabetic efficacy in streptozotocin-induced diabetic rats, with reduced toxicity and minimal bioaccumulation compared to maltolato- and picolinato-based vanadium species. Structural identity was established by spectroscopic methods. Crystal structures were obtained for four complexes, providing insight into their solid-state chemistry. Stability studies in simulated intestinal and gastric fluids showed that the complexes largely retained their integrity under intestinal conditions, whereas decomposition occurred in the highly acidic gastric environment within several minutes. In vivo experiments revealed a structure-antihyperglycemic activity relationship. The nicotinic-containing complex showed the highest activity, reducing blood glucose levels by 67% within 7 days of treatment, while the remaining complexes improved glycemic control by more than 50%. Bioaccumulation studies demonstrated <1.1% uptake in the liver and kidneys and negligible accumulation in the brain. The presented vanadium compounds enhance antidiabetic potential by addressing key limitations, particularly bioaccumulation and toxicity, associated with vanadium agents previously evaluated in clinical trials.

Digital twins (DTs) are increasingly used to monitor and secure Industrial Control Systems (ICS), yet detecting stealthy False Data Injection Attacks (FDIAs) that manipulate system states within normal physical bounds remains challenging. Deep learning anomaly detectors often over-generalize such subtle manipulations, while classical fault detection methods do not scale well in highly correlated multivariate systems. We propose a closed-loop Information-Theoretic Digital Twin (IT-DT) framework for real-time anomaly detection. N4SID identification is combined with steady-state Kalman filtering to quantify residual distribution shifts via closed-form KL divergence, capturing both mean deviations and malicious cross-covariance shifts. Evaluations on the SWaT and WADI datasets show that IT-DT achieves F1-scores of 0.832 and 0.615, respectively, with better precision than deep learning baselines such as TranAD. Computational profiling indicates that the analytical approach requires minimal memory and provides approximately a 600x inference speedup over transformer-based methods on CPU hardware. This makes the framework suitable for resource-constrained industrial edge controllers without GPU acceleration.

<p>Aim:</p> <p>To assess the impact of cognitive impairments on various domains of quality of life in patients with multiple sclerosis (MS).</p> <p>Methods:</p> <p>This prospective study included 135 MS patients and 50 healthy controls. Participants were divided into three groups: patients with MS for more than one year (n=85), newly diagnosed MS patients (n=50), and healthy individuals (n=50). Neurocognitive assessments included the Mini-Mental State Examination, Wechsler Intelligence Scale, Revised Beta Test, Raven's Coloured Progressive Matrices, Wechsler Memory Scale, Rey-Osterrieth Complex Figure Test, Verbal Fluency Test, Audio-Verbal Learning Test, and the SF-36 Quality of Life Scale.</p> <p>Results:</p> <p>Cognitive impairments were present in 40&ndash;60% of MS patients, with memory dysfunctions being the most prominent (30&ndash;60%). Longer disease duration was associated with poorer visuospatial, visuoconstructive, and attention-related abilities. Patients also showed reduced logical and working memory. Quality of life was significantly lower in MS groups compared to controls, with a notable correlation between cognitive impairment and decreased MMSE scores.</p> <p>Conclusion:</p> <p>Cognitive impairments in MS patients, particularly those affecting memory, executive functioning, and attention, significantly reduce quality of life. Cognitive testing should be considered essential in assessing disease severity and treatment planning.</p> <p style="text-align: justify; text-justify: inter-ideograph; line-height: 150%;"><strong>&nbsp;</strong></p>

<p><strong>Introduction.</strong>&nbsp;Ruptured abdominal aortic aneurysm (RAAA) is a life-threatening emergency with high mortality. While conventional risk factors are well recognized, emerging evidence suggests environmental temperature may also influence rupture risk. This relationship has not been studied in Bosnia and Herzegovina. The aim of this study is to investigate the association between ambient temperature and RAAA incidence.</p> <p><strong>Methods:</strong>&nbsp;A retrospective observational study was conducted at the Clinical Center of the University of Sarajevo between January 2021 and February 2025. Data from 105 RAAA patients were analyzed using demographic, clinical, and temperature data, with time series analysis assessing patterns around rupture events.</p> <p><strong>Results:</strong>&nbsp;The mean patient age was 71.5 &plusmn; 7.6 years; 86.7% were male. The average aneurysm diameter was 85.1 &plusmn; 17.7 mm. Hypertension (68.6%), smoking (55.2%), and diabetes (37.7%) were the most prevalent comorbidities. The mortality rate was 38.7%. Most ruptures occurred during colder months, with a peak in January (16.1%) and a low in August, March, and February (each 4.7%). The mean ambient temperature during the 10 days before rupture was 11.41 &plusmn; 6.16 &deg;C, not significantly different from the temperature on the rupture day (p = 0.991). However, minimum daily temperature was significantly lower than the mean daily temperature on rupture days (6.48 &plusmn; 5.92 &deg;C vs. 11.42 &plusmn; 17.61 &deg;C; p &lt; 0.001).</p> <p><strong>Conclusion:</strong>&nbsp;A seasonal RAAA pattern with winter clustering was observed, but no consistent short-term link to ambient temperature was found, warranting further study with advanced models.</p>

The expansion of industrialization and household use of synthetic compounds has generated significant wastewater containing toxic heavy metals. In developing countries, this wastewater is often discharged untreated due to the high cost of advanced treatment technologies. This study used sodium hydroxide as a low-cost, readily available precipitation agent to remove selected metal ions from mono- and binary-component solutions. Unlike most studies focusing on pH and initial ion concentration, this work investigated operational parameters such as stirring speed (0–800 rpm) and time (0–30 min) while keeping pH and concentration constant. Results showed that higher stirring speeds and longer stirring times enhanced metal ion removal, with Pb(II) efficiency increasing from 86.64% at 100 rpm to 94.33% at 800 rpm. In binary mixtures, similar improvements were observed. These findings highlight that simple, low-cost operational adjustments can significantly improve metal removal efficiency, which is particularly relevant for water treatment in resource-limited settings. The two-way ANOVA without replication showed that the type of metal or mixture had a significant effect on removal efficiency, while stirring speed and time within the investigated ranges did not have a statistically significant effect. These results indicate that differences in removal efficiency are primarily due to the metals’ chemical properties rather than the operational parameters.

China’s export-oriented economic expansion has substantially influenced transport-sector CO2 emissions, raising critical concerns about the environmental impacts of sustained industrial growth and global trade integration. Understanding the interplay between macroeconomic dynamics, trade composition, and industrial structure is essential for aligning economic development with climate mitigation objectives. This study examines transport-related CO2 emissions in China over the period 1990–2023, employing a hybrid methodological framework that combines econometric modeling—including Autoregressive Distributed Lag (ARDL) bounds testing, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS)—with machine-learning techniques using Extreme Gradient Boosting (XGBoost) interpreted through SHapley Additive exPlanations (SHAP). The analysis confirms a long-run cointegration relationship between transport emissions and the selected macroeconomic variables. Short-run dynamics indicate a strong sensitivity of emissions to GDP growth, while long-run estimates reveal that higher export-to-GDP ratios and industrial value added contribute to reducing transport emissions, reflecting the efficiency gains from industrial upgrading and cleaner trade practices. By contrast, the expansion of medium- and high-technology exports increases emissions due to the energy- and logistics-intensive nature of high-value goods. The XGBoost model achieves high predictive performance, with an out-of-sample R2 of 0.9975 and a Root Mean Square Error (RMSE) of 87.16, confirming the dominant contribution of medium- and high-technology exports to transport-sector emissions. The results underscore the critical role of aligning trade structure, industrial productivity, and low-carbon logistics within China’s policy agenda. Implementing strategies that enhance industrial energy efficiency and develop sustainable transport infrastructure can substantially reduce the environmental impacts associated with export-driven economic expansion.

Background/Objectives: COVID-19 severity is influenced by a complex interplay between host, viral, and environmental factors. Emerging evidence suggests that Neanderthal-derived genetic variants may influence the progression and severity of SARS-CoV-2 infection. This study aimed to evaluate the association between selected Neanderthal-derived variants and COVID-19 severity in the population of the Republic of Srpska, considering relevant clinical, sociodemographic, and lifestyle factors. Methods: This multicentric cross-sectional study included 402 participants, classified as healthy or SARS-CoV-2-positive individuals. A total of 378 COVID-19-positive participants were further stratified according to disease severity and hospitalization status. All individuals were genotyped for the Neanderthal-derived OAS3 rs1156361 (C/T) and LZTFL1 rs35044562 (A/G) variants. Detailed sociodemographic, clinical, and lifestyle data were also collected. Results: A higher frequency of the LZTFL1 rs35044562 AG genotype was observed among hospitalized patients compared with non-hospitalized individuals (36.8% vs. 20.9%; p = 0.005), while the AA genotype was more prevalent among non-hospitalized patients (77.3% vs. 63.2%, p = 0.015). Multivariable logistic analysis showed that carriers of the LZTFL1 AG genotype had a higher chance of hospitalization compared to AA carriers (adjusted OR = 1.372, 95% CI = 0.763–6.383, and p = 0.021). Hospitalized patients more frequently carried the combined CT (OAS3) and AG (LZTFL1) genotypes, supporting a potential synergistic effect. Several sociodemographic factors, including age, sex, education, employment, and urban residence, were also associated with COVID-19 severity, while no significant associations were observed in allele-based analyses. Conclusions: LZTFL1 gene polymorphisms may influence COVID-19 severity, with heterozygote-specific and combined risk effects observed. These preliminary findings are exploratory and require validation in larger cohorts, but may guide future studies and targeted interventions in high-risk groups.

The Open and Reproducible Musculoskeletal Imaging Research (ORMIR) community is a scientific community dedicated to promoting openness and reproducibility in musculoskeletal imaging, image processing, and computational modelling. In this perspective paper, we outline the motivations for conducting transparent research and provide practical guidelines to implement it. We start with defining open and reproducible research and describing the benefits and challenges of working transparently. Next, we redefine the outputs of a computational research study as—ideally—a combination of data, code, and a publication, recommend a folder and file structure that reflects these three study outcomes, and describe how to maintain and update such a structure during the study and at study publication. Finally, we emphasize that working in an open and reproducible manner is a learning process and the best way to acquire the necessary competencies is simply to start. Lay summary: The ORMIR community promotes openness and reproducibility in musculoskeletal imaging research. In this perspective paper, we explain why transparency matters and recommend how to conduct a computational study in an open and reproducible manner focusing on its three outputs: data, code, and publication. Finally, we highlight that the best way to learn these practices is simply to start.

BACKGROUND Inflammation-driven mechanisms play a central role in adverse outcomes after non-ST-elevation myocardial infarction (NSTEMI), yet simple, widely available biomarkers for early risk stratification remain insufficiently defined. Hemogram-derived indices and iron-related inflammatory markers may provide complementary prognostic information. OBJECTIVE To evaluate the prognostic significance of the mean platelet volume-to-monocyte ratio (MMR) and serum ferritin in predicting major adverse cardiovascular events (MACE) in patients with NSTEMI, and to assess the association of angiotensin-converting enzyme (ACE) inhibitor therapy with clinical outcomes. METHODS This prospective cohort study included 170 consecutive NSTEMI patients admitted to the University Clinical Center Tuzla between February 2022 and January 2023. All patients received dual antiplatelet therapy and high-intensity statins. The baseline evaluation included a complete blood count, serum ferritin, and C-reactive protein. MMR was calculated as the ratio of mean platelet volume to absolute monocyte count. Patients were followed for 12 months for the occurrence of MACE, defined as cardiovascular death, non-fatal myocardial infarction, urgent revascularization, stroke, or hospitalization for heart failure. RESULTS During follow-up, 103 patients (60.6%) experienced MACE. Admission MMR (18.1 ± 11.7 vs 13.2 ± 5.5; P = 0.003) and ferritin levels (284 ± 396 vs 152 ± 109 µg/L; P = 0.001) were significantly higher in patients with events. In multivariable analysis, both MMR (odds ratio [OR] 1.06, 95% confidence interval [CI] 1.02-1.11; P = 0.008) and ferritin (OR 1.28 per 100 µg/L, 95% CI 1.10-1.55; P = 0.003) independently predicted MACE, while ACE inhibitor therapy was associated with a lower risk (OR 0.24, 95% CI 0.08-0.70; P = 0.01). The combined model demonstrated good discriminative performance (AUC 0.72; 95% CI 0.64-0.80). CONCLUSION AND RELEVANCE Elevated admission MMR and ferritin were independently associated with a higher 1-year risk of MACE in patients with NSTEMI. ACE inhibitor therapy was associated with improved outcomes, although causality cannot be inferred. These findings suggest that readily available inflammatory biomarkers may complement established clinical parameters for early risk stratification and support continued guideline-directed pharmacotherapy in NSTEMI.

Introduction Glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1) are increasingly used biomarkers in the evaluation of mild traumatic brain injury (mTBI), primarily to reduce the frequent overuse of head computed tomography (head CT). However, their specificity may be compromised by orthopedic trauma, which commonly accompanies mTBI. The aim of this study was to assess whether orthopedic trauma is associated with higher serum concentrations of GFAP and UCH-L1 in CT-negative mTBI patients, thereby potentially reducing their specificity for detecting CT-positive mTBI. Materials and methods This prospective observational study included 67 CT-negative mTBI patients, of whom 29 (0.43) had orthopedic trauma and 38 (0.57) had none. Blood samples were obtained within 12 hours of injury and serum concentrations of GFAP and UCH-L1 were measured using a chemiluminescent microparticle immunoassay (CMIA) on the Alinity analyzer, following the manufacturer's instructions. Statistical analysis included Mann-Whitney U test, chi-square test, Kruskal-Wallis test, post-hoc Dunn's test and logistic regression analysis with P < 0.05 considered significant. Results Serum GFAP concentrations were significantly higher in patients with orthopedic injuries (median (IQR): 70.0 (30.8 to 226.5) pg/mL) than in those without (24.95 (5.52 to 49.15) pg/mL; P < 0.001). Similarly, UCH-L1 concentrations were higher in the orthopedic injury group (median (IQR): 2494.3 (670.1 to 5708.1) pg/mL) compared with those without trauma (262.8 (153.8-595.3) pg/mL; P < 0.001). Conclusions Orthopedic trauma is associated with higher serum concentrations of GFAP and UCH-L1 in CT-negative mTBI patients, which may reduce the specificity of these biomarkers for ruling out intracranial injury.

Proton pump inhibitors (PPIs) are widely used for the treatment of acid-related disorders, but inappropriate or prolonged use carries potential health risks. Physicians, due to their access to medication and clinical knowledge, may be prone to self-medicating with PPIs without appropriate oversight. To assess the prevalence and patterns of personal PPI use and self-medication among practicing physicians in Bosnia and Herzegovina, and to identify demographic and professional predictors of such behavior. A cross-sectional, questionnaire-based survey was conducted among 448 physicians who responded to the study invitation, out of approximately 600 invited, from various healthcare levels in Bosnia and Herzegovina between January and May 2025. The survey collected data on PPI use history, consultation behavior, awareness of adverse effects, and adherence to treatment guidelines. Multivariable logistic regression was used to identify independent predictors of self-medication. A total of 65.4% of respondents reported past PPI use, during their medical practice, and 31.7% were current users. Over half (52.2%) admitted using PPIs without consulting another physician, and only 17.4% referred to clinical guidelines prior to use. Occasional use was the most common pattern (59.0%), while adverse effects were rarely reported (1.8%). No demographic or professional variable was significantly associated with self-medication with PPIs (defined as PPI use without consulting another physician) in the multivariable analysis. Self-medication with PPIs is highly prevalent among physicians and frequently occurs without clinical consultation or adherence to guidelines. This behavior appears to be widespread across age groups, sexes, and care levels, highlighting the need for institutional interventions that promote rational prescribing and raise awareness about responsible self-care within the medical profession.

Severe hypoglycemia increases the risk of cardiovascular disease (CVD) in people with diabetes. Large cohort studies and scientific statements show that severe hypoglycemia is linked to higher rates of coronary heart disease, cardiovascular events, and mortality in both type 1 and type 2 diabetes. This risk is especially high in individuals with significant vascular risk, such as older adults and those with multiple cardiovascular risk factors. Hypoglycemia triggers several pathophysiological changes that increase cardiovascular risk. These include activation of the sympathoadrenal system, promotion of proinflammatory and prothrombotic states, arrhythmogenic changes, and increased hemodynamic stress. Experimental evidence shows that recurrent hypoglycemia worsens microvascular dysfunction and promotes adverse cardiac remodeling, especially in people with diabetes. While the link between hypoglycemia and cardiovascular events is well established, the causality remains debated. Hypoglycemia may directly contribute to cardiovascular disease or indicate underlying vulnerability, especially in patients with advanced disease or comorbidities. Minimizing hypoglycemic episodes is recommended for all patients with diabetes, particularly those with established cardiovascular disease, due to the clear association with adverse outcomes.

In this paper, we study the dynamics and bifurcation of a two-dimensional discrete-time predator-prey model. The existence and local stability of the equilibrium points of the model are analyzed algebraically. It is shown that the model can undergo a transcritical bifurcation at equilibrium point on the $x$-axis and a Neimark-Sacker bifurcation in a small neighborhood of the unique positive equilibrium point. Some numerical simulations are presented to illustrate our theoretical results.