Background Differentiation of leukocytes is one of the key diagnostic procedures in clinical medicine, and correct identification of them in a blood smear is of essential importance. Light microscopy is the reference method for leukocyte differentiation; however, it is time-consuming and must be performed by a highly qualified specialist. For this reason, automatic analysers capable of precise and accurate differentiation of blood cells in the examined sample are increasingly present in haematology laboratories. This paper aims to evaluate the performance of the Sysmex XN-3100 analyser, manufactured by SYSMEX CORPORATION, Kobe, Japan., with a focus on the advantages and disadvantages of its digital microscopy in the differentiation of leukocytes and give brief guidelines on the possibilities and limitations of everyday work on the basis of the obtained results. Methods Digital optical microscopy on 253 samples was performed with primary data (preclassification) collected after the completion of the autoanalysis. Before validating the obtained results, the data were reviewed by a medical biochemistry specialist who confirmed or corrected them. This generated secondary data (reclassification). The two groups of data were statistically analysed using Passing-Bablok regression analysis, Bland-Altman analysis and Spearman correlation. Results The obtained results showed strong correlations between the primary and secondary analysis in all cells (highest in lymphocyte group (r=0.986), lowest in eosinophil group (r=0.870)) except immature granulocytes and blasts (significant deviation from linearity, p<0.01). Conclusions The haematology analyser Sysmex XN-3100 shows high performance in leukocyte analysis and differentiation using digital microscopy, but samples containing blasts and immature granulocytes must additionally be analysed by light microscopy.

The Trends in International Mathematics and Science Study (TIMSS) is a large-scale international assessment that measures students’ achievement in mathematics and science at the fourth and eighth-grade levels. Coordinated by the International Association for the Evaluation of Educational Achievement (IEA), TIMSS is conducted every four years. The 2023 assessment represented the eighth cycle of TIMSS, collecting data from 64 participating countries. This exploratory study examines the influence of several key factors—gender, home learning resources, experiences of bullying, disruptive classroom behavior, and students’ sense of school belonging—on fourth-grade mathematics achievement in Bosnia and Herzegovina. The research sample included 2,712 students (mean age: 10.2 years; SD = 0.4; 1,388 girls and 1,324 boys). Results showed that home learning resources were the most important predictor of mathematics achievement, emphasizing the essential role that home educational conditions play in student academic outcomes. The observed difference between boys and girls in mathematics scores was minimal. Both bullying and disruptive behavior were found to have a statistically significant negative impact on mathematics performance, whereas the effect of students’ sense of school belonging did not reach statistical significance. Home learning resources proved to be the most decisive variable in forecasting mathematics achievement among fourth-grade students in Bosnia and Herzegovina, reinforcing the value of home-based educational support in fostering academic progress. These results suggest the necessity for educational policies and interventions that ensure fair access to learning resources within the home environment. The paper concludes with a discussion of the implications of these findings and outlines potential avenues for future research and educational practice.

In our letter, we presented the challenges within medical biochemistry in a tertiary hospital in a measles outbreak. The letter somewhat shows the current situation in the first part. In the remaining part, the challenges in the work of the medical biochemical laboratory are listed and the significance of the most common biochemical and hematological analyzes for these patients is explained. This letter is an important clinical-epidemiological overview of the current situation that arose as a result of the measles outbreak.

This letter proposes a multi-stream selection framework for \ac{CF-MIMO} networks. Partially coherent transmission has been considered by clustering \acp{AP} into phase-aligned clusters to address the challenges of phase misalignment and inter-cluster interference. A novel stream selection algorithm is developed to dynamically allocate multiple streams to each multi-antenna \ac{UE}, ensuring that the system optimizes the sum rate while minimizing inter-cluster and inter-stream interference. Numerical results validate the effectiveness of the proposed method in enhancing spectral efficiency and fairness in distributed \ac{CF-MIMO} networks.

Zeolitic materials incorporating mono- and bimetallic systems of nickel and cobalt were obtained from natural zeolite modified with Ni2+ and Co2+ chloride solutions through traditional ion exchange (IE) and impregnation (Imp) processes. Special attention was given to analyzing the cationic and anionic composition of the resulting materials. The catalytic potential was evaluated in the selective hydrogenation of citral, focused on the formation of unsaturated alcohols. The IE process replaced mainly Ca2+ and Na+ with Ni2+ and Co2+ cations in the zeolite phases (clinoptilolite and mordenite mix), while Imp resulted in higher metal content (2.0–2.7%) but retained significant amounts of chloride (1.9–3.8%), as confirmed by XRD and temperature-programmed reduction. The materials prepared by IE had negligible chloride content (0.02–0.07%), and their specific surface areas (138–146 m2/g) were greater than those of the materials obtained by Imp (54–67 m2/g). The bimetallic systems exhibited enhanced reducibility of the Co2+ and Ni2+ isolated cations, attributed to synergistic interactions that weakened the cation–framework binding. Catalytic activity tests showed that nickel species were primarily responsible for citronellal formation. Among all materials, the bimetallic CoNiIE catalyst, prepared by IE, was the only one to produce unsaturated alcohols, suggesting that synergistic Ni–Co interactions played a role in their formation.

Athlete nutrition is an important aspect of training itself. Athletes must take sufficient amounts of all nutrients (carbohydrates, fats, and proteins) on a daily basis, as well as vita-mins and minerals that often have a crucial impact on the quality of training. Daily calories vary depending on the intensity of training, gender, and body weight of the individual. Satis-faction with daily caloric needs is crucial in maintaining constant body weight, achieving fast recovery after activity, and growth and regeneration of skeletal muscles. The objective of the study was to determine the differences in eating habits of users of two different fitness cen-ters. The study included 90 subjects of both genders and different ages. Fitness centers are different according to the type of exercise they practice: CrossFit and classic fitness centers. The survey was specially designed for this type of research. In one fitness center, the survey was conducted "live" and in another “online”. The results of the research showed that there is no statistically significant difference between the respondents of the fitness center who practice classical fitness and those who practice CrossFit when choosing foods and the frequency of their use. It was also found that there was no statistically significant difference in water intake on a daily basis between the respondents of both fitness centers

Hypericin, a tumour-selective photosensitizer, has shown potential in cancer therapy, but its poor water solubility has limited clinical use. To address this, we developed a water-soluble variant called high hypericin-loaded polyvinylpyrrolidone (HHL-PVP) to enhance hypericin's applicability, particularly for treating glioblastoma, a typically terminal disease. We tested HHL-PVP in both in vitro and in vivo models, first confirming its fluorescent properties in the lab and then assessing its efficacy in more complex animal models. Using subcutaneous and orthotopic tumour mouse models, we combined HHL-PVP administration with fluorescence-guided surgery and photodynamic therapy (PDT) to target residual tumour cells. Histological analysis of both healthy and tumour tissue showed HHL-PVP's over 97 % sensitivity and 100 % specificity in distinguishing tumour tissue. In subcutaneous glioblastoma models, significant tumour necrosis and remission occurred after HHL-PVP administration and a 20-minute white light application through the skin. These results highlight HHL-PVP's effectiveness in targeting and eradicating glioblastoma cells. Our findings provide strong evidence that HHL-PVP is a promising therapeutic option for glioblastoma, with its high sensitivity, specificity, and potential for tumour remission through PDT. This approach warrants further investigation in clinical trials and could improve outcomes for a disease that has been difficult to treat.

Due to the increasing demand for effective and objective analysis to address complex challenges such as brain medical image reconstruction, segmentation, and classification, medical image analysis for brain tumor research has gained significant attention. The ability of Generative Adversarial Networks (GANs) to increase the probability density over data distributions by estimating density ratios, along with their capacity to uncover high-dimensional latent distributions, has led to substantial performance improvements in visual feature extraction. Furthermore, the adversarial loss incurred by the discriminator offers a subtle method of incorporating unlabeled samples into training, thereby improving accuracy at higher orders. These characteristics of GANs have proven valuable in various applications, including enhancing medical images and translating images across different modalities. Additionally, the ability of GANs to generate images with remarkable realism offers hope that, through these generative models, the ongoing challenge of limited labelled data in the medical field may be overcome. The aim of this review is to provide a comprehensive overview, starting with a concise summary of the range of available GAN architectures and datasets. This study then highlights the research conducted in processing and interpreting GAN-based brain images. Finally, the limitations of GAN-based methods for brain image analysis are discussed, identifying unresolved research issues and suggesting avenues for further exploration in this emerging field.

As the use of autonomous mobile robots expands into dynamic and complex environments, the need for them to provide understandable explanations for their actions becomes crucial. This thesis addresses the challenge of developing explainability for robot navigation by leveraging a hybrid model that combines machine learning techniques with symbolic reasoning methods. Furthermore, the thesis explores the modeling of human explanation preferences and the impact of different explanation attributes on explanation recipients' understanding, satisfaction, and trust. The goal is to integrate different explanation aspects and approaches into a unified framework to support explainable navigation in robotics.

AimCOVID-19 pandemic, caused by SARS-CoV-2, has had a profound impact on global health, including in Bosnia and Herzegovina, which faced unique challenges due to limited testing and high mortality rates. This analysis aimed to identify mutations and detect different SARS-CoV-2 lineages across four pandemic waves.MethodologyA total of 127 SARS-CoV-2 samples were collected and sequenced from patients from the Federation of Bosnia and Herzegovina, providing a comprehensive overview of the viral genetic diversity in this region. Two sequencing platforms, Ion Torrent and Illumina, were used, whereby 37 samples were sequenced on the Ion Torrent platform, while others were sequenced on the Illumina platform.ResultsThis study presents a genomic analysis of SARS-CoV-2 variants circulating in the Federation of Bosnia and Herzegovina over four distinct pandemic waves, spanning from March 2020 to April 2023. Examination of genomic variations across these waves revealed key mutations associated with transmission and potential virulence.ConclusionThese genomic insights into SARS-CoV-2 evolution in Federation of Bosnia and Herzegovina emphasizes the importance of continuous surveillance to understand viral evolution and strengthen public health responses to future pandemics.

Differentiating sequencing errors from true variants is a central genomics challenge, calling for error suppression strategies that balance costs and sensitivity. For example, circulating cell-free DNA (ccfDNA) sequencing for cancer monitoring is limited by sparsity of circulating tumor DNA, abundance of genomic material in samples and preanalytical error rates. Whole-genome sequencing (WGS) can overcome the low abundance of ccfDNA by integrating signals across the mutation landscape, but higher costs limit its wide adoption. Here, we applied deep (~120×) lower-cost WGS (Ultima Genomics) for tumor-informed circulating tumor DNA detection within the part-per-million range. We further leveraged lower-cost sequencing by developing duplex error-corrected WGS of ccfDNA, achieving 7.7 × 10−7 error rates, allowing us to assess disease burden in individuals with melanoma and urothelial cancer without matched tumor sequencing. This error-corrected WGS approach will have broad applicability across genomics, allowing for accurate calling of low-abundance variants at efficient cost and enabling deeper mapping of somatic mosaicism as an emerging central aspect of aging and disease. This work integrates duplex sequencing with cost-effective Ultima sequencing to enhance the accuracy of whole-genome circulating cell-free DNA profiling.

Understanding the impact of vegetation on organic matter content in sediments is essential for sustainable reservoir management and water quality protection. This study examined the relationship between land cover, erosion processes, and organic matter accumulation in the sediments of four small water reservoirs in the Republic of Serbia. Organic matter content was quantified and analyzed in relation to basin characteristics, including land-use composition, absolute and mean flow gradients, and sediment grain size distribution. Field sampling was conducted across the catchments of four small water reservoirs—Duboki potok, Resnik, Ljukovo, and Sot—with sediment samples collected from main tributaries and accumulation basins. A multi-method approach was employed, combining remote sensing for vegetation-cover assessment, granulometric analysis, organic matter evaluation via loss-on-ignition at 350 °C, and statistical correlation analysis to assess the influence of land use and hydrological gradients on sediment composition. The results revealed a strong correlation (R = 0.892) between forest cover and sedimentary organic matter content, confirming the significant role of vegetation in stabilizing sediments and promoting organic matter deposition. Reservoirs with higher forest and shrub cover (e.g., Sot and Duboki potok) exhibited greater organic matter accumulation (5.79–5.98%), while the agriculture-dominated Ljukovo catchment (76.85% agricultural land) recorded the lowest organic matter content (3.89%) due to increased sediment displacement and reduced erosion resistance. These findings underscore the critical role of vegetation in regulating sediment dynamics and enhancing organic matter retention in small water reservoirs. To mitigate excessive organic matter deposition and improve water quality, sustainable watershed management strategies—such as vegetation buffer strips, afforestation, and erosion control measures—are recommended.

Rosemary ( Rosmarinus officinalis L.) is a valuable medicinal and aromatic herb produced for its bioactive compounds and commercial applications. However, commonly used methods for rosemary propagation have various limitations that impose the need to create appropriate protocols for in vitro propagation of this species. This research aimed to evaluate the effects of light quality and plant growth regulators (PGRs) on rosemary micropropagation. Explants were cultured on Murashige and Skoog (MS) medium supplemented with varying concentrations of 6-benzylaminopurine (6-BAP), meta-Topolin (mT), 1-naphthaleneacetic acid (NAA), and indole-3-butyric acid (IBA), under different light treatments: fluorescent light (FL) and blue (BL), red (RL), and red-blue (RBL) LED lights. The highest fresh mass was formed by explants grown in medium with mT at 1.0 mg/L + 0.1 mg/L NAA under BL (88.05 ± 2.94 mg), while FL with the same PGR combination resulted in the highest dry mass (12.89 ± 0.55 mg). FL, in combination with 1.0 mg/L mT + 0.1 mg/L NAA, produced the highest number of new shoots (2.07 ± 0.04), and RL, in combination with cytokinin-free MS medium, induced the longest shoots (13.16 ± 0.37 mm). The highest number of nodes (3.91 ± 0.08) was recorded under BL in the cytokinin-free medium. For in vitro rooting, BL combined with 0.1 mg/L mT + 0.5 mg/L IBA produced the highest rooting percentage (80.00 ± 5.77%), the highest number of roots (3.92 ± 0.15), and the longest roots (75.30 ± 1.76 mm). This treatment also resulted in the highest plantlet establishment rate (71.13 ± 4.43%), confirming the synergy between BL and mT + IBA in improving the efficiency of rosemary rooting and acclimatization. These results enable a more straightforward selection of the optimal light spectrum and PGR concentrations for individual stages of the rosemary micropropagation process and highlight the potential of LED lights as a more efficient alternative to traditional fluorescent lamps. What is already known about this subject? Previous research on various plant species has shown that light quality and PGRs are important factors in regulating and directing multiplication, rooting, and general development of in vitro plants. LED lights, especially those in the blue and red spectra, showed positive effects on the processes of photomorphogenesis and, in general, the growth and development of explants. However, research on the micropropagation of rosemary has usually been focused on callus formation and active compound production and rarely on developing effective protocols for producing high-quality planting material. What are the new findings? This research showed the potential of LED lighting to outperform standard fluorescent light during in vitro rosemary propagation. Also, mT was found to be more effective than 6-BAP in promoting shoot proliferation and multiplication. To the best of our knowledge, this is the first study to simultaneously investigate the synergistic effects of light quality and PGRs on rosemary micropropagation. What are the expected impacts on horticulture? The findings of this research provide an efficient and integrated approach to the in vitro propagation of rosemary. Energy-efficient LED lights and optimal PGR combinations allow commercial growers to produce high-quality planting material.

OBJECTIVE Traumatic dental injuries (TDI) are among the most common public health issues in dentistry. The dentist's role in the immediate treatment of traumatic injuries is crucial, as it impacts the long-term outcome of treatment and the patient's quality of life. Dentists should have good knowledge of dentoalveolar trauma to be ready to act promptly in emergencies and to be able to provide appropriate guidance and advice to eyewitnesses or injured individuals at the scene of an accident. This study aimed to assess the level of knowledge regarding TDI among dental students and dentists. MATERIALS AND METHODS Participants included fourth- and sixth-year dental students, dentists, oral surgery residents and specialists, with a response rate of 61.99% from 1059 participants. Data collection involved face-to-face and email methods. Quantitative data analysis utilised Student's t-test and ANOVA, while categorical data was analysed using Pearson chi-square test, with RStudio and Excel for data analysis. RESULTS Dental students had a mean score of 15.0 ± 4.7, indicating the highest theoretical knowledge of TDI compared to other examined groups. However, 83.5% reported never experiencing TDI. Oral surgical residents scored lowest at 7.8 ± 2.3. Interestingly, dentists with less than 5 years of experience outperformed those with 5-10 years of practice. Most participants (92.4%) prioritised direct tooth replacement, but only 67.7% identified proper tooth-preserving media, and just 38.0% understood the ideal splint for avulsed teeth. CONCLUSION While dental students demonstrated a strong understanding of TDI management, there are areas needing further education, especially among oral surgical residents. Since TDI knowledge tends to decline throughout the years of practice, continuous education on TDI for dental practitioners is essential.