University Clinical Hospital Mostar (Croatian: Sveučilišna klinička bolnica Mostar) is the largest hospital in Mostar, Bosnia and Herzegovina. It is situated in the Bijeli Brijeg neighbourhood of the city, although Clinic for infectious diseases, Clinic for skin and sexually transmitted diseases and Physiatry clinic are located in the town center in the former Surgery department building. The hospital was originally built as a regional medical centre in 1977. However, the building incurred damage during the war in Bosnia and Herzegovina and upon its repairs, it was upgraded into a hospital in 1997.Since 1997 the hospital has cooperated with the University of Mostar's Medical Faculty in training medical professionals.
Non-small cell lung cancer (NSCLC) remains the leading cause of cancer mortality worldwide; however, precision oncology has fundamentally transformed its treatment landscape. In 2025, seven approvals by the U.S. Food and Drug Administration (FDA) further accelerated biomarker-driven care across critical molecular subsets. These include MET-directed and trophoblast cell-surface antigen-2 (TROP-2) antibody-drug conjugates (ADCs), expanded strategies targeting epidermal growth factor receptor (EGFR), notably those addressing exon 20 insertion mutations, a ROS proto-oncogene 1 (ROS1) inhibitor, and various human epidermal growth factor receptor 2 (HER2) options that encompass both tumor-agnostic and mutation-selected approaches. These advancements underscore the necessity for integrated diagnostics—such as next-generation sequencing (NGS), fluorescence in situ hybridization (FISH), and immunohistochemistry (IHC)—while also emphasizing ongoing challenges in biomarker selection, therapeutic sequencing, and equitable global implementation.
Background:Functional dyspepsia (FD) is a common gastrointestinal (GI) disorder which significantly impacts quality of life and subjective well-being (SWB). Psychosocial factors have been linked to FD symptoms, which places this disorder among the "disorders of gut-brain interaction." Recent studies suggest notable sex differences in symptom expression and the level of disruption of daily activities. This study aims to explore the impact of sex on associations between psychological factors and SWB in individuals with FD. Methods:The study included 191 adults referred to their first endoscopic examination of the upper GI tract due to dyspeptic symptoms. Patients completed validated measures assessing GI symptoms, GI and extra-GI comorbidities, health-related habits, psychological traits (somatization, stress resilience), and indicators of SWB (life satisfaction, positive and negative experiences). Multiple regression and hierarchical block regression analyses were conducted to identify predictors of SWB and to examine the potential moderating role of sex and psychological factors. Subsequently, path analysis was conducted to explore potential causal pathways among sex, psychological variables and SWB. Results:Participants displayed relatively homogeneous characteristics according to sex. Two main subgroups were identified: a larger group of highly educated, working-age individuals and a smaller group of older adults (>60 years) with higher comorbidity levels. Psychological factors, stress resilience and somatization emerged as the strongest predictors of SWB, while health and lifestyle factors had modest effects. Sex was identified as a significant determinant of SWB in the complex hierarchical model, but only after controlling for somatization and stress-resilience. The path model indicated that other sex-related factors may also influence SWB. Conclusion:Results pointed toward the need to involve psychological constructs like somatization and stress resilience in studies examining SWB in individuals with FD. The importance was highlighted of examining the gender-related (socially conditioned) factors associated with SWB, and the need to separately assess these factors in older and younger individuals with FD (<60, ≥60). The study revealed a complex interactive network between age, gender, and SWB-related factors, supporting the biopsychosocial model of FD. However, identifying a suitable methodological framework to elucidate these complex relationships remains a challenge.
BackgroundLarge language models (LLMs) are increasingly being studied as potentially valuable support tools in oncology practice including clinical decision support. Yet, their real-world utility in melanoma treatment decision-making is still not sufficiently considered, especially in resource-limited settings. Accordingly, this study evaluated the performance of four LLMs against real-world treatment decisions of a melanoma multidisciplinary tumor board (MDT).MethodsThis retrospective single-center study included 151 consecutive patients with newly diagnosed cutaneous melanoma discussed at the MDT at the University Clinical Center Tuzla, Bosnia and Herzegovina, between 2020 and 2024. Melanoma treatment recommendations generated by four LLMs, ChatGPT-4o, ChatGPT-5 Thinking, Gemini 2.5 Pro and DeepSeek-V3.2, were evaluated by four board-certified oncologists against the actual MDT treatment decisions. Additionally, the LLM-generated recommendations were also rated across five pre-specified domains: clarity, clinical applicability, coverage, explanation and support with evidence, and guideline concordance.ResultsIn this study, inter-rater reliability was acceptable to good, supporting the consistency of expert evaluation. ChatGPT-5 Thinking showed the strongest and most consistent overall performance, followed by ChatGPT-4o, while Gemini 2.5 Pro and DeepSeek-V3.2 were rated less favorably. Differences between LLMs were statistically significant across all evaluated domains. Performance differences appeared most clinically relevant in more complex scenarios, particularly when consideration of adjuvant or systemic treatment strategies was required.ConclusionThe findings of this study suggest that selected LLMs may have a supportive role in everyday melanoma MDT practice particularly in oncology centers with limited resources. However, the current results do not support the use of LLM-generated recommendations as independent treatment decisions, and further prospective studies are required before LLM-assisted treatment recommendations can be safely integrated into the MDT workflow.
Kinesiology, as the scientific study of human movement, has undergone substantial conceptual and structural changes over the past decades. According to Mraković, kinesiology is defined as an empirical, experimentally based science that studies the laws, principles, and patterns of controlled and purposeful physical activity and its effects on the human organism. This definition highlights the scientific and systematic nature of the discipline. The aim of this review paper is to examine the development of kinesiology in the 21st century, with particular emphasis on its paradigm shift from a practice-oriented field toward an interdisciplinary scientific discipline. The analysis is based on foundational and contemporary literature, including empirical and systematic studies . The findings suggest that kinesiology has evolved into a comprehensive field integrating biological, social, and behavioural sciences. Modern kinesiology focuses on health, performance, and human development, addressing global challenges such as physical inactivity and chronic disease. The discipline is increasingly recognised as a central scientific framework for understanding human movement in the 21st century. The review further demonstrates that the future development of kinesiology will depend on interdisciplinary collaboration, methodological standardization, international scientific cooperation, and the integration of emerging technologies such as wearable sensors, artificial intelligence, motion analysis systems, and precision exercise medicine. These developments position kinesiology as a central scientific discipline for addressing contemporary challenges in health, human performance, and physical activity across the lifespan.
Drug-induced renal injury (DIRI) remains a substantial issue in clinical practice, contributing to high morbidity, mortality, socioeconomic and healthcare cost. Traditional markers, such as serum creatinine or blood urea nitrogen, have low specificity and sensitivity for early identification, underscoring the need for new reliable biomarkers. This chapter investigates biomarker improvements for DIRI, focusing on clinical uses, limitations, and future possibilities. The chapter examines biomarkers such as neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, cystatin C, β2-microglobulin and clusterin for diagnosing nephrotoxicity. In addition, we highlight the role of proteomics and metabolomics in facilitating the identification and development of novel biomarker candidates via high-throughput ultra-sensitive technology in investigating DIRI mechanisms. The chapter discusses validation frameworks, regulatory criteria for biomarker adoption in clinical settings, and how they are integrated into treatment monitoring and personalized medicine. Case examples demonstrate the real-world applicability in early diagnosis, risk classification, and therapy optimization. Standardization, cost, and translational gaps are discussed, as well as the potential for artificial intelligence and machine learning to improve biomarker processing and interpretation. Finally, this chapter emphasizes the transformative potential of DIRI biomarkers in providing a pathway to more accurate and timely identification of renal injury, improved patient outcomes, and reduced healthcare costs. Future research and global collaboration are required to fully realize the potential of these advances in clinical and regulatory settings.
