Background: The etiology of oral ulceration is multicausal with numerous predisposing factors. Studies by various authors cite Helicobacter pylori infection as a possible cause of certain oral ulcerations. Objective: The aim of the study is to prove the presence of Helicobacter pylori in the oral cavity of patients with oral ulcerations, as well as to examine the relationship between the presence of Helicobacter pylori in the oral cavity and the development of oral ulcerations. Methods: The study included regular patients at the Department and Clinic of Oral Medicine and Periodontology, Faculty of Dental Medicine, University of Sarajevo, suffering from oral ulcerations, as well as healthy patients without oral diseases. The diagnosis of oral ulceration is based on a thorough history, clinical examination, and exclusion of other oral diseases. All patients were taken anamnestic data on the existence of digestive system diseases, and by reviewing medical documentation, a previously diagnosed digestive system disease by a gastroenterologist was recorded. A cytological smear was taken in all 80 cases, in patients with ulcerative lesions a smear was taken from the lesion and in healthy subjects from the mucous membrane of the palate, cheek and tongue. Highly sensitive and specific polymerase chain reaction (PCR) was used to determine the presence of Helicobacter pylori in the oral cavity and oral lesions. Results: The results of our study showed that there is no statistically significant difference between the presence of Helicobacter pylori in the oral cavity of patients with oral ulcerations and subjects with healthy mucosa. Conclusion: Helicobacter pylori is not a risk factor for the development of oral ulcerations and can be found on the oral mucosa as a transient pathogen.

Background: Normal sleep duration is crucial for maintaining brain homeostasis. Sleep disorders in Parkinson's disease are numerous, multifactorial, and result in significant morbidity. Objective: The aim of the study was to investigate the association between gender and the duration of therapy on sleep quality in patients with Parkinson's disease. Methods: The study is prospective, and includes 40 consecutively hospitalized patients with verified Parkinson's disease. The study included subjects of both genders and all age groups. To analyze the data on the subjects, we used: medical histories, nursing documentation of patients, a questionnaire with sociodemographic data, and the Parkinson's Disease Sleep Assessment Scale. We divided all subjects into two groups: subjects who have been using therapy for up to 5 years and those who have been using therapy for more than 5 years. Results: Among subjects who have been taking medication for less than 5 years, 33.3% were female and 66.6% were male. Of the total number of respondents who have been taking therapy for more than 5 years, 36.3% are female and 63.6% are male. The duration of the therapy has a statistically significant effect on the quality of sleep in patients with Parkinson's disease (p < 0.05). The subject's gender does not have a significant independent influence on the quality of sleep in patients with Parkinson's disease (p > 0.05). The interaction of gender and length of therapy use has no significant separate effect on the quality of sleep in Parkinson's disease patients (p > 0.05). The quality of sleep is better in male and female subjects who take the therapy until the age of 5. Conclusion: The duration of therapy use has a significant impact on the quality of sleep in Parkinson's disease patients. The gender of the subject has no significant independent influence on the quality of sleep in patients with Parkinson's disease.

Background: Peripheral arterial disease (PAD) is a chronic condition of reduced blood flow through the arteries. Early detection and prevention of PAD, especially in at-risk populations, is crucial to reducing morbidity and mortality. Objective: The aim of the study was to examine the clinical feasibility of vascular ultrasound screening for early detection of PAD, as well as potential financial savings through preventive measures. Methods: The study was conducted as a prospectively designed cross-sectional study with retrospective sample analysis, in which the sample consisted of 826 patients over 60 years of age, of both sexes, divided into two groups, conducted from January 2023 to May 2024. Results: The study included 826 patients aged 60 and over, divided into two groups after ultrasound examination of the arteries (Group A with atherosclerosis /63.8%/; Group B - without atherosclerosis /36.2%/). The average age was 65.44±5.9 years, 60-65 years was 64.3%, and over 65 years was 35.7%. A statistically significant difference was recorded between the analyzed groups in terms of comorbidities and risk factors. We found that age, gender, hypertension, hyperlipidemia, diabetes, smoking and chronic obstructive disease have a significant relationship with the degree of atherosclerosis. Multivariate analysis showed that the age of the subjects, hyperlipidemia, hypertension and smoking are significant predictors of atherosclerosis. The prevalence for hemodynamically significant stenosis of ACI/ACC was 5.0%, for peripheral arteries 4.2%, the prevalence of aneurysm abdominal aorta (>3 cm) was 2.3%, and 0.5% for diameter >5 cm. Conclusion: The results show the high efficiency of ultrasound diagnostics in identifying asymptomatic patients with advanced atherosclerosis, emphasizing the need for better organization of preventive programs, which could lead to potential savings in healthcare costs through earlier detection and treatment.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has underscored the significant role of cardiovascular risk factors in determining the severity and outcomes of the disease. Pre-existing conditions such as hypertension, diabetes, obesity, and cardiovascular diseases have emerged as key contributors to increased susceptibility to severe forms of COVID-19, influencing both short-term and long-term health outcomes. This review examines the complex interplay between these risk factors and the virus’s direct impact on the cardiovascular system. Key findings suggest that conditions like hypertension, diabetes, and obesity not only predispose individuals to more severe disease but also exacerbate complications such as myocardial injury, arrhythmias, and heart failure. Furthermore, the long-term cardiovascular effects of COVID-19, including myocarditis and pericarditis, are of growing concern, particularly in patients with pre-existing cardiovascular conditions. The virus’s ability to induce myocardial damage through mechanisms involving ACE2 receptor binding and inflammatory cytokine storms has been well-documented. The pandemic has also highlighted significant cardiovascular complications, including left and right ventricular dysfunction, myocardial injury, and elevated pulmonary arterial pressure, with the right ventricle being particularly affected due to pulmonary damage. Imaging modalities such as echocardiography and cardiac magnetic resonance have proven valuable for diagnosing myocardial injury and complications, although accessibility may be limited in routine clinical practice. Survivors of severe COVID-19, especially those with pre-existing cardiovascular conditions, face an elevated risk of major adverse cardiovascular events for up to two years post-infection. Evaluation of post-COVID patients includes ECGs, laboratory tests, echocardiography, and cardiac MRI, which provide critical insights into myocardial injury and complications. Preventive measures, including vaccination, regular monitoring of cardiovascular health, and lifestyle modifications, play a crucial role in reducing the long-term risk of cardiovascular complications. The role of vaccination in mitigating the risk of severe disease and cardiovascular complications is well-established, despite rare cases of vaccine-related myocarditis. Understanding these interactions is essential for developing targeted management strategies, improving patient outcomes in both acute and long-term COVID-19 effects, and addressing the broader challenges posed by COVID-19’s impact on cardiovascular health.

Background/Aim: The aim of this study was to conduct a comparative analysis of the oral health promotion programmes in the Balkan countries, to compare key measures and activities in the implementation of the programme, and to analyse the results achieved after the implementation of the programme. Material and Methods: Data were obtained through an electronic search of publicly available documents published in the field of dental healthcare in the Balkan countries. The search terms were: "national programme", "strategy", "action plan", "project", and "oral health". The search was conducted in English and in the native languages of the Balkan Peninsula countries. A comparative analysis of valid documents and those whose validity period has expired was carried out. Results: This study illuminates the information on preventive programmes for each country and discusses the challenges faced in the Balkans region. While countries in the Balkan Peninsula have made progress in improving the oral health of their inhabitants, the absence of national oral health promotion programmes is striking. Greater involvement of the community in activities to maintain and improve oral health is needed, as is more comprehensive dental care for vulnerable populations. Conclusions: The findings of this study may be employed to enhance oral health in the delineated regions, and to confer benefits upon the population of the region and beyond. The findings from this analysis provide valuable insights for policymakers and public health professionals aiming to strengthen oral health initiatives and ensure more equitable access to dental care across the Balkan Peninsula. This paper (Part II) describes specifics of oral health promotion programmes, dental health care, and key epidemiological indicators in each Balkan country.

Background: The prevalence of obesity and obesity-related clinical conditions, including metabolic-associated steatotic liver disease (MASLD), sarcopenia, and a wide spectrum of pathological manifestations, is rising globally. According to WHO, BMI is the only anthropometric measure currently used to classify obesity, overweight, and underweight. However, emerging research suggests that obesity is a complex pathological state influenced by multiple etiological factors. Given the limitations of BMI, there is a growing need for a more comprehensive assessment of body composition, particularly fat mass quantity and distribution. Bioelectrical impedance analysis (BIA) provides valuable anthropometric data that can help differentiate obesity phenotypes and guide improved therapeutic approaches. Objective: This study aims to analyze body composition using BIA in a randomly selected sample of adults from primary healthcare settings in Bosnia and Herzegovina. The primary goal is to assess total body weight, fat mass quantity, fat distribution, and obesity types prevalent in this population. Additionally, the study seeks to establish reference values for further diagnostic, preventive, and therapeutic strategies to improve public health outcomes. Methods: A cross-sectional study was conducted on adults (≥18 years) in Gračanica, Bosnia & Herzegovina (B6H), from January 2021 to January 2025. Inclusion criteria required participants to provide signed informed consent, while exclusion criteria included acute systemic diseases, severe dehydration, and fasting for more than 24 hours. Anthropometric parameters measured included age, height, weight, BMI, body fat mass (BFM), fat-free mass (FFM), percent body fat (PBF), waist-hip ratio (WHR), and bone mineral content (BMC). Data were analyzed using SPSS (version 18), with results presented as medians, interquartile ranges, and percentiles (5th, 25th, 50th, 75th, and 95th). Results: A total of 4,628 adults participated in the study, of whom 2,824 (61.0%) were female and 1,804 (39.0%) were male. The median age was 45 years (IQR: 29 years). The findings revealed that over one-quarter of the B&H population is obese, with abdominal obesity being the predominant type. This phenotype is associated with the highest risk for metabolic syndrome and MASLD. Conclusion: Our study highlights a high prevalence of obesity among the examined individuals in primary care settings in B&H, with abdominal obesity being the most common type. This phenotype is strongly associated with metabolic complications. BIA-derived parameters of fat distribution and visceral fat mass may serve as valuable tools for improving obesity classification and developing more effective preventive and therapeutic strategies.

Project risk management is one of the project management knowledge areas that identifies, analyzes and deals with project risks. One of the important factors influencing the decision-making of a project-based organization is the level of risk tolerance of organization. This study focuses on the factors affecting the level of risk tolerance of project-based organizations. For this purpose, in the first step, the potential factors affecting risk tolerance are extracted by reviewing the related literature. In the next step, the factors affecting the organization's risk tolerance level are identified by using the Fuzzy Delphi method in several steps. The most effective factors are identified by experts? judgment using a questionnaire. Then, the relationships between these factors are determined by using the Interpretive Structural Modeling (ISM) method. The intensity of these relationships and the intensity of the effect of the factors are investigated by using the Fuzzy DEMATEL method. Finally, the factors are ranked based on their weights by utilizing the Fuzzy DEMATEL method. In this study, 13 external and internal factors are ranked using questionnaires based on the experts? opinions. Four external factors include political conditions and international relations, the conditions of the capital markets such as stock market, investment security and government support. These factors have significant influence on the other factors as well as the project-based organization. The findings of this study direct project managers to accurately identify the risk tolerance level of the key project stakeholders in order to efficiently plan and implement project risk management and achieve project goals.

Background/Aim. Piclidenoson (CF101, IB-MECA), a selective agonist of the A3 adenosine receptor (A3AR), is used in clinical trials for the treatment of psoriasis. Emerging data from in vitro and in vivo studies suggest that piclidenoson possesses anti-inflammatory and immunomodulatory properties, but its action on human peripheral blood mononuclear cells (PBMCs) remains unknown. The aim of this study was to examine the anti-inflammatory effects of piclidenoson in a model of phytohaemagglutinin (PHA)-stimulated human PBMCs culture. Methods. Human PBMCs were isolated from the venous blood of healthy donors (n = 4) and treated with different concentrations of piclidenoson. Flow cytometry and the 3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide (MTT) test were used to determine cell viability, while the MTT method and the carboxyfluorescein succinimidyl ester (CFSE) staining method were used to analyze the effect of picl idenoson on cell proliferation. Levels of tumor necrosis factor (TNF)-?, interleukin (IL)-6, IL-1?, IL-23, IL-36, IL-5, interferon (IFN)??, IL-17, and IL-10 were measured using a specific sandwich enzyme-linked immunosorbent assay (ELISA). Results. The results of cytotoxicity tests showed that the highest applied concentration of piclidenoson (1,500 nM) reduced the metabolic activity of PBMCs (p < 0.05) and increased the percentage of late apoptotic (p < 0.05) and necrotic cells (p < 0.01). Non-toxic concentrations (250, 500, and 1,000 nM) decreased the proliferation of PBMCs (p < 0.05) compared to the control cells. These concentrations also decreased the production of TNF-? (p < 0.001). Piclidenoson at concentrations of 250 and 1,000 nM reduced the production of IL-23 (p < 0.05) while the concentrations of 500 and 1,000 nM reduced the production of IL-36 (p < 0.05). Piclidenoson at 1,000 nM increased IL-1? production, while other concentrations decreased its production (p < 0.01). The highest concentration (1,000 nM) inhibited the production of IL-5 (p < 0.05) and IFN-? (p < 0.01) while all applied concentrations inhibited the production of IL-17 (p < 0.001). Furthermore, piclidenoson increased the production of IL-10 in all applied concentrations (p < 0.01). Conclusion. At non-toxic concentrations, piclidenoson exerts anti-inflammatory properties associated with the inhibition of proliferation and modulation of cytokine production in PHA-stimulated PBMCs culture.

Ovaj rad u svom uvodnom dijelu nudi informaciju o dvodnevnoj međunarodnoj naučnoj konferenciji Institucija hifza Kur’ana u Bosni i Hercegovini, o njenom značaju, učesnicima i izloženim radovima. U drugom dijelu se fokusira, kao nastavak tematici Konferencije, na temu odnosa između hifza Kur’ana i razumijevanja značenja njegovog teksta. Govori se o dilemi šta je za muslimana važnije: memorisanje Teksta ili njegovo razumijevanje. Nudi se odgovor na tu dilemu i nudi metoda učenja hifza uz razumijevanje sadržaja. Na kraju se predlaže određeni oblik druženja hafiza jednog područja na programu analize odabranih odlomaka iz Kur’ana i preuzimanje ponuđenih pouka i principa iz njega važnih za praktični život muslimana uopće, a posebno hafiza kao primjernih individua ovog ummeta.

Selecting a tractor is one of the most complex investment decisions an agricultural producer faces. There are numerous types of tractors on the market, each differing in technical, economic, and ecological characteristics. The aim of this research is to demonstrate how multi-criteria analysis methods can aid in this decision-making process, using a practical example of selecting an optimal tractor for the Myzeqe area in Albania. In this study, a decision-making model was developed based on a hybrid fuzzy methodology, combining the fuzzy LOPCOW (Logarithmic Percentage Change-Driven Objective Weighting) and fuzzy MABAC (Multi-Attributive Border Approximation Area Comparison) methods. The findings show that the determination of criterion weights is less crucial, with the T15 tractor exhibiting the best overall indicators. This research primarily contributes to developing a methodology in agriculture that enhances production outcomes.

This paper aims to generalize linear models for the multiproduct break-even point. Taking into consideration identified research gaps, the paper focuses on deriving formulas for determining the multiproduct break-even point through determination models. Different assumptions regarding the constancy of individual product contribution structures to total physical production volume, total revenue, total variable costs, and total contribution margin are taken into account. Additionally, connections between the obtained solutions from different models and different assumptions regarding the constancy of individual product contributions are established. The verification of the optimality of solutions obtained through different determination models is conducted by comparing them with solutions derived from linear programming as a benchmark. The developed models are tested using a case study of a multiproduct company in the metal processing industry. Through comparative analysis, the hypotheses concerning obtaining an optimal solution and the identical nature of solutions derived from the determination model and linear programming are examined. This paper contributes to the understanding of the multiproduct break-even point, providing a theoretical and practical framework for evaluation and enabling the application of various determination models in the context of a multiproduct situation.

Providing an objective ranking of scientists based on their merit is a rather challenging task. Numerous factors complicate this endeavor, raising difficult questions about how such evaluations should be conducted. The goal of the present paper is to introduce a new measure for evaluating researchers’ performance, the Performance Impact Score (PIS), which combines both productivity and research impact. In this study, I compared the PIS with h-index scores for 108 researchers at the University of Sarajevo. More specifically, I examined the overlap between the top 20 researchers according to the PIS and the top 20 researchers according to Web of Science, Google Scholar, and SCOPUS h-indexes. The concordance rate was 65% for Google Scholar and Web of Science, and 55% for SCOPUS. The analysis highlights the importance of considering both productivity and impact when evaluating researchers’ rankings. It is also evident that the top 20 researchers vary across different metrics. The results further demonstrate that creating a fair and just ranking system requires going beyond the data available in bibliometric databases, particularly in cases where researchers rank highly by one metric but perform poorly when evaluated by another.

he study aims to assess the capability of various data mining techniques in detecting inaccurate financial statements of government-owned enterprises operating in the Federation of Bosnia and Herzegovina (FBiH). Inaccurate financial statements indicate potential financial fraud. Prediction models of four classification algorithms (J48, KNN, MLP, and BayesNet) were examined using a dataset comprising 200 audited financial statements from government-owned enterprises under the supervision of the Audit Office of the Institutions in the Federation of Bosnia and Herzegovina. The results obtained through data mining analysis reveal that a dataset encompassing seven balance sheet items provides the most comprehensive depiction of financial statement quality. These seven attributes are: opening entry of accounts receivable, profit (loss) at the end of the period, operating assets at the end of the period, accounts receivable at the end of the period, opening entry of operating assets, short term financial investments at the end of the period, and opening entry of short-term financial investments. By employing these seven attributes, the MLP algorithm was implemented to construct the most precise predictive model, achieving a 76% accurate classification rate for financial statements. Leveraging the identified attributes, a mathematical model could potentially be formulated to effectively predict financial statements of government-owned enterprises in FBiH. This, in turn, could considerably facilitate the process of selecting GOEs for inclusion in the annual work plan of state auditors. Presently, due to resource constraints, government-owned enterprises in FBiH do not undergo regular annual scrutiny by state auditors, with only 10 to 15 such enterprises being subject to audits each year. The results of this research can also be beneficial to both the public and the Financial Intelligence Agency in the FBiH. The paper contributes to filling the gap in the literature regarding the applied methodology, particularly in the part concerning the attributes used in the research.