Psychological studies on close relationships have often overlooked cultural diversity, dynamic processes, and potentially universal principles that shape intimate partnerships. To address the limited generalizability of previous research and advance our understanding of romantic love experiences, mate preferences, and physical attractiveness, we conducted a large-scale cross-cultural survey study on these topics. A total of 404 researchers collected data in 45 languages from April to August 2021, involving 117,293 participants from 175 countries. Aside from standard demographic questions, the survey included valuable information on variables relevant to romantic relationships: intimate, passionate, and committed love within romantic relationships, physical-attractiveness enhancing behaviors, gender equality endorsement, collectivistic attitudes, personal history of pathogenic diseases, relationship quality, jealousy, personal involvement in sexual and/or emotional infidelity, relational mobility, mate preferences, and acceptance of sugar relationships. The resulting dataset provides a rich resource for investigating patterns within, and associations across, a broad range of variables relevant to romantic relationships, with extensive opportunities to analyze individual experiences worldwide.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder that affects the entire personality and is most often diagnosed during school age. The Tomatis Method involves neurosensory brain stimulation through unique listening programs. The aim of this study was to examine the impact of the Tomatis Method on the attention of a child with ADHD. The listening program was tailored to the child's specific needs and was administered by a certified Tomatis practitioner. Each treatment cycle lasted 14 days. The assessment was conducted at four time points: before and after the first cycle, and before and after the second cycle of the Tomatis treatment. A software-based assessment tool specifically designed to evaluate components of executive functions was used to measure attention. The collected data were processed using IBM SPSS Statistics 21 software for statistical analysis. Basic statistical parameters were calculated. The results showed improvements in attention-related abilities, including increased response accuracy and faster reaction times. Key words:Tomatis Method, ADHD, attention.

Purpose Diabetic kidney disease (DKD) significantly affects health and healthcare costs due to chronic kidney disease complications. Given asprosin’s potential as a biomarker for disease progression, we conducted the first systematic review and meta-analysis on its relationship with DKD in adults with type 2 diabetes mellitus (T2DM). Methods PubMed, Embase, Cochrane, and Web of Science were systematically searched. Standard mean differences (SMD) with 95% confidence intervals (CI) and Fisher’s Z transformation were used to examine the relationship between asprosin and DKD. The risk of bias was evaluated using the Newcastle-Ottawa Scale (NOS) and its version for cross-sectional studies. Heterogeneity (I² > 50%) was analyzed with a random-effects model. Results Six studies (n = 1340) were included. Meta-analysis results indicated that T2DM patients with DKD (micro/macroalbuminuria) had significantly higher circulating asprosin levels than normoalbuminuric T2DM patients (SMD: 1.5, 95% CI: 0.69–2.32, p = 0.0003). Meta-analysis of correlation revealed a positive association of asprosin with urinary albumin excretion ratio (UACR) (Fisher’s Z = 0.4; 95% CI: 0.240–0.554, p < 0.001) and body mass index (BMI) (Fisher’s Z = 0.17; 95% CI: 0.036–0.301, p = 0.013), and a negative association with estimated glomerular filtration rate (eGFR) (Fisher’s Z = −0.35; 95% CI: −0.471 to −0.239, p < 0.001). Conclusion Asprosin is elevated in T2DM patients with pre-DKD (early stage DKD) and DKD and correlates with key markers of disease severity. Additional research is required to better understand the pathophysiological mechanisms of asprosin and its role in DKD.

Abstract Polygenic risk scores (PRS) combine the effects of multiple genetic variants to predict an individual’s genetic predisposition to a disease. PRS typically rely on linear models, which assume that all genetic variants act independently. They often fall short in predictive accuracy and are not able to explain the genetic variability of a trait to the full extent. There is growing interest in applying deep learning neural networks to model PRS given their ability to model non-linear relationships and strong performance in other domains. We conducted a survey of the literature to investigate how neural networks model PRS. We categorize deep learning-based approaches by their underlying architecture, highlighting their modeling assumptions, likely strengths and potential weaknesses of the architectures. Several categories of neural network architectures exhibited promising signs for the improvement of PRS’ predictive power, namely sequence-based architectures, graph neural networks and those that incorporated biological knowledge. Additionally, the use of latent representations in autoencoders has improved predictive performance across diverse ancestries. However, a lack of existing model benchmarks on consistent datasets and phenotypes makes it challenging to understand the extent to which different architectures improve performance. Interpretability of deep learning-based PRS is also challenging with great care required when inferring causation. To address these challenges, we suggest the establishment and adherence to reporting standards and benchmarks to aid the development of deep learning-based PRS to find quantifiable trends in neural network architectures.

Menopause represents an inevitable transition in a woman’s life, presenting with vasomotor symptoms, mood disorders, sleep difficulties, and prolonged risks such as osteoporosis and cardiovascular diseases. Hormone replacement therapy emerged as the cornerstone of menopausal management, particularly for alleviating symptoms and preventing postmenopausal osteoporosis. However, findings from the Women’s Health Initiative (WHI) study in 2002 highlighted increased risks of breast cancer, cardiovascular disease, and stroke associated with hormonal replacement treatment, leading to a significant global decline in its usage. Consequently, numerous women were deprived of essential therapy, endangering their health and quality of life. This review presents the findings of the WHI study, discusses its methodological errors, and evaluates its benefits and harms. We explore landmark studies that have reestablished the benefits and risks of hormone replacement therapy over the past two decades. Guidelines supported by these findings are presented in this review. Despite advancements, public perception of hormone replacement treatment remains influenced by outdated findings, limiting its utilization in many regions, especially in developing countries. Our objective is to provide evidence that misconceptions about hormone replacement therapy significantly impact women’s general health and quality of life, as well as to clarify the short-term and long-term impacts of hormone replacement therapy. We conclude that hormonal replacement treatment is effective and safe when administered according to established guidelines. Access to information, coupled with knowledgeable physicians who consistently interact with women, is as vital as the contributions of menopause healthcare specialists. Conflicting information from outdated professionals can likely lead to treatment failure in patients. Keywords: menopause, women’s health, estrogens, progestins, quality of life

The conducted research aimed to determine the dietary habits of elderly people. The research was conducted on a sample of 237 respondents differentiated by gender, 133 males and 104 females and by age 65 -89 years. Data processing was done in the SPSS program and descriptive and comparative statistics were used to obtain data. Descriptive parameters were created for the analysis of the factual state of the respondents. The collected data were analyzed using the Microsoft Excel 2007 tool, and are presented in tables. It is evident that the health status of the respondents worsens with age, and dietary habits change in a positive sense with age. Given that the world's population is aging, it is necessary to emphasize attention to certain needs and challenges faced by many older people. Nutrition is an important element of health in the elderly population and affects the aging process. Although it is a study on a relatively small number of subjects, in comparison with a larger European study, it becomes relevant for proving the present problem of malnutrition among elderly patients. It is necessary to take all measures to increase the awareness of health workers about this problem in order to successfully prevent it or stop it in time.Looking at the entire sample of respondents globally, we can conclude that overall, a significant number of respondents do not pay enough attention to the structure of foods in their diet and water consumption.In line with previous research, the results of this study highlight the importance of dietary habits in creating a healthy lifestyle and preventing chronic non-communicable diseases. Key words:eating habits, age, respondents, differences, lifestyle

Introduction. Sentinel lymph node biopsy (SLNB) has significantly advanced axillary staging in clinically node-negative breast cancer, offering lower morbidity compared to traditional axillary lymph node dissection (ALND). Nonetheless, precise prediction of non-sentinel lymph node (non-SLN) involvement remains essential for optimizing surgical decisions and preventing unnecessary ALND. Methods. A retrospective cohort analysis was performed on 176 patients with clinically node-negative breast cancer who underwent SLNB. Clinicopathological data were reviewed to evaluate associations between various predictive factors and non-SLN involvement. Variables analyzed included tumor size, histological grade, lymphovascular invasion (LVI), Ki-67 proliferation index, and sentinel lymph node characteristics. Results. Multivariable logistic regression identified the type of SLN metastasis (OR=21.4; 95% CI 1.7–43.6; p=0.01), the number of positive SLNs (OR=5.66; 95% CI 1.18–36.6; p=0.03), and the number of negative SLNs (OR=0.04; 95% CI 0.006–0.27; p=0.001) as independent predictors of non-SLN metastases. The predictive model demonstrated excellent discriminatory power, with an area under the receiver operating characteristic curve (AUC) of 0.91. Conclusion. Specific clinical and histopathological variables reliably predict non-SLN involvement in SLN-positive breast cancer patients. Incorporation of these predictors into clinical practice may enhance individualized axillary management and reduce unnecessary ALND procedures. Further validation through larger prospective studies is warranted. Key words: Breast Neoplasms, Sentinel Lymph Node Biopsy, Axillary Lymph Nodes, Lymph Node Dissection, Neoplasm Staging.

Background Non-ST-elevation myocardial infarction (NSTEMI) is frequently associated with systemic inflammation and metabolic dysregulation. Indices derived from routine laboratory tests that reflect systemic inflammatory and lipid-inflammatory status may offer better prognostic insight. This study aimed to evaluate the association between selected indices and short-term major adverse cardiovascular events (MACE) and all-cause mortality in patients with NSTEMI treated with dual antiplatelet therapy (DAPT) and statin. The selected indices reflect key mechanisms involved in NSTEMI pathophysiology, including insulin resistance, atherogenic dyslipidemia, and inflammation. Materials and methods This prospective observational study included 171 patients with NSTEMI admitted to the Intensive Care Unit of the Clinic for Internal Medicine at the University Clinical Centre Tuzla between February 1, 2022, and January 31, 2023. Blood samples were collected upon admission and 24 hours subsequently. The following indices were calculated: triglyceride-glucose index (TyG), triglyceride-to-high-density lipoprotein ratio (TG/HDL), atherogenic index of plasma (AIP), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and pan-immune-inflammation value (PIV). Outcomes were tracked during hospitalization and up to three months post-discharge. MACE was defined as cardiovascular death, reinfarction, stroke, or unplanned revascularization. All patients underwent coronary angiography; revascularization was performed when clinically indicated. Exclusion criteria included active malignancy, infection, or inflammatory disease. Logistic regression was adjusted for age, diabetes, and other clinical variables. Missing data were handled using the pairwise deletion method. Results High levels of TyG at admission were independently associated with MACE (odds ratio (OR) 1.7; 95% confidence interval (CI) 1.0-2.8; p = 0.037). All-cause mortality occurred in 14.6% of patients (n = 25), while MACE occurred in 60 patients. Independent predictors of mortality included elevated TyG at admission (OR 2.2; 95% CI 1.1-4.4; p = 0.034), TG/HDL at 24 hours (OR 1.4; 95% CI 1.1-1.7; p = 0.007), AIP at 24 hours (OR 5.7; 95% CI 1.1-28.9; p = 0.035), and NLR at 24 hours (OR 1.1; 95% CI 1.0-1.2; p = 0.002). PLR and PIV at 24 hours were also significantly associated with mortality. Optimal cut-off values were TyG ≥ 8.9, AIP ≥ 0.35, and NLR ≥ 4.5. NLR had the highest estimated area under the curve (AUC ≈ 0.78). Conclusion In NSTEMI patients treated with DAPT and statin, several inflammatory and lipid-inflammatory indices were independently associated with short-term mortality. Indices measured at 24 hours had a stronger prognostic value than baseline values. Serial monitoring may aid early risk stratification. Outcomes were assessed during hospitalization and via structured follow-up up to three months post-discharge.

This work proposes a motion planning algorithm for robotic manipulators that combines sampling-based and search-based planning methods. The core contribution of the proposed approach is the usage of burs of free configuration space ($\mathcal{C}$-space) as adaptive motion primitives within the graph search algorithm. Due to their feature to adaptively expand in free $\mathcal{C}$-space, burs enable more efficient exploration of the configuration space compared to fixed-sized motion primitives, significantly reducing the time to find a valid path and the number of required expansions. The algorithm is implemented within the existing SMPL (Search-Based Motion Planning Library) library and evaluated through a series of different scenarios involving manipulators with varying number of degrees-of-freedom (DoF) and environment complexity. Results demonstrate that the bur-based approach outperforms fixed-primitive planning in complex scenarios, particularly for high DoF manipulators, while achieving comparable performance in simpler scenarios.

Summary The rapid rise of 3D printing, both in industrial and home settings, presents emerging health and environmental risks. While 3D printing enhances sustainability by reducing waste and optimizing resource use, its impact on human health remains poorly understood. The use of metals and polymers linked to health risks, coupled with the release of inhalable particles and volatile organic compounds, raises concerns about respiratory and systemic effects. The absence of clear guidelines creates high public demand for information and limits safe implementation, particularly in schools and homes where millions of 3D printers are expected by 2030. Additionally, improper disposal of 3D printing polymer materials may exacerbate plastic pollution. This article proposes the perspective of a structured risk assessment framework set on particle emissions from industrial 3D printing. It will offer a practical tool to bridge current knowledge gaps and to inform safe practice and policy development, because immediate action is necessary to balance innovation with safety.

Narrative review synthesizes the most current literature on the SARS-CoV-2 XEC variant, focusing on its genomic evolution, immune evasion characteristics, epidemiological dynamics, and public health implications. To achieve this, we conducted a structured search of the literature of peer-reviewed articles, preprints, and official surveillance data from 2023 to early 2025, prioritizing virological, clinical, and immunological reports related to XEC and its parent lineages. Defined by the distinctive spike protein mutations, T22N and Q493E, XEC exhibits modest reductions in neutralization in vitro, although current evidence suggests that mRNA booster vaccines, including those targeting JN.1 and KP.2, retain cross-protective efficacy against symptomatic and severe disease. The XEC strain of SARS-CoV-2 has drawn particular attention due to its increasing prevalence in multiple regions and its potential to displace other Omicron subvariants, although direct evidence of enhanced replicative fitness is currently lacking. Preliminary analyses also indicated that glycosylation changes at the N-terminal domain enhance infectivity and immunological evasion, which is expected to underpin the increasing prevalence of XEC. The XEC variant, while still emerging, is marked by a unique recombination pattern and a set of spike protein mutations (T22N and Q493E) that collectively demonstrate increased immune evasion potential and epidemiological expansion across Europe and North America. Current evidence does not conclusively associate XEC with greater disease severity, although additional research is required to determine its clinical relevance. Key knowledge gaps include the precise role of recombination events in XEC evolution and the duration of cross-protective T-cell responses. New research priorities include genomic surveillance in undersampled regions, updated vaccine formulations against novel spike epitopes, and long-term longitudinal studies to monitor post-acute sequelae. These efforts can be augmented by computational modeling and the One Health approach, which combines human and veterinary sciences. Recent computational findings (GISAID, 2024) point to the potential of XEC for further mutations in under-surveilled reservoirs, enhancing containment challenges and risks. Addressing the potential risks associated with the XEC variant is expected to benefit from interdisciplinary coordination, particularly in regions where genomic surveillance indicates a measurable increase in prevalence.

This study investigated the potential of high-voltage electrical discharge (HVED), as a green, non-thermal extraction technology, for recovering polyphenols from winter savory (Satureja montana L.). Key process parameters, including frequency (40, 70, 100 Hz) and extraction time (1, 5, 15, 30, 45 min), were optimized, using water as a solvent and maintaining a constant solid-to-liquid ratio of 1:100 g/mL. The extracts were characterized for total polyphenol content (TPC), total flavonoid content (TFC), and antioxidant activity (DPPH, ABTS, FRAP), while individual phenolics were quantified via HPLC-DAD. Multivariate chemometric analyses, including Pearson correlation, heatmap clustering, and principal component analysis (PCA), were employed to reveal relationships between extraction conditions, polyphenolic profiles, and antioxidant activities. The results showed strong correlations between TPC, TFC, and antioxidant activity, with compounds such as quercetin-3-D-galactoside, procyanidin A2, and rutin identified as key contributors. Among the tested conditions, extraction at 70 Hz for 45 min provided the highest polyphenol yield and bioactivity. The application of HVED demonstrated its potential as an efficient and environmentally friendly technique for obtaining phenolic-rich extracts. In addition, the use of chemometric tools provided useful insights for optimizing extraction conditions and understanding the contributions of specific compounds to bioactivity. These results support future applications in clean-label product development and contribute to broader efforts in sustainable ingredient production for the food, cosmetic, and nutraceutical sectors.

This scientific research work investigates the social and legal protection of unaccompanied and separated children from the population of migrants, refugees and asylum seekers in the municipality of Velika Kladušafrom 2019 to 2022. The research is based on data collected from government records, reports from non-governmental organizations and interviews with key actors, including social workers, lawyers and representatives of civil society organizations. The research reveals that unaccompanied and separated children in Velika Kladuša face significant challenges in accessing social and legal protection. Many of these children experience trauma, violence and exploitation during the journey, but also in Bosnia and Herzegovina, and continue to face significant risks and vulnerabilities upon arrival. Despite the established legal and political frameworks for the protection of these children, the ability of institutions and services to respond to their needs is limited, and many children fall through gaps in the system.The research highlights the need for increased resources, funding and training for institutions and service providers working with unaccompanied and separated children. It also highlights the importance of a holistic, child-centred approach to social and legal protection, which takes into account the specific needs and vulnerabilities of this population. Ultimately, this research provides important insights and recommendations for improving the social and legal protection of unaccompanied and separated children in the municipality, and contributes to broader efforts to ensure the rights and well-being of all children on the move. Key words: unaccompanied and separated children, migrants, refugees, asylum seekers, social and legal protection, risks, vulnerabilities, institutions, services, capacities, child-centred approach, resources, policy frameworks, recommendations.

It can be stated that quality is an integral part of our daily life. All people constantly insist on quality in certain areas of life, which indicates that quality can be found in all segments in which a person work. The main objective of this study is to examine the satisfaction of clients/users with the services of spa centers. The basic research methods used are: synthesis, analysis, induction and deduction, comparative and statistical methods. The collection of primary data was carried out through an online survey, which contains a standardized scale (SERVQUAL). The correlation analysis confirms the general objective, so it can be concluded that the Pearson coefficient is -0.158, from which it follows that there is a very weak negative correlation between these two variables. It is concluded that sociodemographic factors do not at all influence the attitude of respondents about the quality of service of spa resorts. But, Pearson coefficient indicates a high degree of correlation between respondents' satisfaction with the quality of service in sparesorts and other factors. There is a very high degree of correlation between respondents' satisfaction with service quality and other factors -81%, which have an impact on the respondents' satisfaction with thequality of service in the spa: the first contact in the spa, the reason for coming to the spa, the distance from home to the spa, travel time and the manner the therapy is introduced. Key words: Quality, safety of services, spa resorts, Bosnia and Herzegovina

The paper aims to identify and analyze effective strategies aimed at managing autistic behaviorand learning barriers. A qualitative analysis of the relevant scientific and professional literature published in the last decade was carried out, and after screening, 41 papers were included in thematic analysis. Strategies are divided into six categories: Behavioral interventions and behavior management, Education of children and youth with ASD and the empowerment of educators, Teaching social skills, Sensory integration therapies, Digital and assistive technologies, and Transition support. All included strategies are evidence-based practices (EBPs). The literature review confirms that there is no universal approach in working with children and youth with ASD. Still, successful intervention is based on the application of a combination of strategies adapted to the individual needs of students, the educational environment, and developmental goals. Despite the multitude of strategies at a given setting's disposal effective implementation of EBPs is often thwarted by system, school, and individual factors suchas limited resources, training, as well as consistency across environments. By addressing these challenges in a comprehensive manner—through inclusive pedagogy, adaptive technology, and collaborative support systems—we can bridge the research-practice gapand provide rich, enabling learning experiences for students with autism spectrum disorders. Key words: autism, learning strategies, behavior management, learning barriers