Introduction: The ankle joint is primarily a hinge joint that allows the foot to bend downwards and upwards, formed by three bones: the tibia (shin bone), fibula (shin bone) and talus (ankle bone). The ankle joint is provided with strength by ligaments, muscles and their tendons. Most ankle ligament injuries occur during sports activities or while walking on an uneven surface that forces the foot and ankle into an unnatural position. The degree of ligament injury depends on the action of force, pressure, fiber composition and torsion. Common clinical symptoms for all ankle injuries are swelling, pain to the touch, possible bruising, local hyperthermia (increased temperature), difficulty walking, limited and painful movements in the joint itself. Objective: The objective of the research is to examine the role of physiotherapy in the treatment of patients with different degrees of trauma to the ankle ligaments. Subjects and methods: Subjects of both genders and all age groups were included in the research in the period from January 2022 to October 2022 with different degrees of ankle ligament injury, which implies different traumatological treatment. After the primary treatment, the subjects were referred for physiotherapy in the physical therapy department at the RMC Safet Mujic Cantonal Hospital and at the Stari Grad Health Center. Results: According to the degree of mobility of the ankle joint of subjects treated conservatively, after physiotherapy treatment we can see that in a total sample of 77 subjects, 76 subjects or 98.70% were without contracture, and 1 or 1.30% had a pronounced contracture. Conclusion: Physiotherapy proved to be effective in reducing pain and improving the mobility of the ankle joint in patients with different degrees of ligament injury, confirming the success of conservative treatment.

Introduction: The aim of this study was to assess the antioxidant activity of cinnamon extracts obtained using different solvents (ethanol, methanol, acetone, water) and their mixtures with water. Additionally, the phenolic and flavonoid contents were analyzed to investigate their correlation with antioxidant activity. Materials and Methods: Cinnamon extracts were prepared using pure solvents (ethanol, methanol, acetone, water) and their mixture with water in different proportions. The total phenolic and flavonoid contents, as well as the antioxidant activity of the obtained extracts, were analyzed. Results and Discussion: The results showed that the extracts obtained from mixtures of ethanol and water had a high content of phenols and flavonoids, with the 40:10 ethanol-to-water mixture yielding the highest phenolic (240.69 mg/g) and flavonoid (0.275 mg/g) contents. Similarly, methanol and its mixtures with water showed variations in the content of these components, with pure methanol providing the highest values (252.12 mg/g for phenols and 0.2212 mg/g for flavonoids). Regarding antioxidant activity, ethanol extracts and their mixtures with water achieved the best results, with the 20:30 ethanol-to-water mixture displaying the highest antioxidant potential (937.775 µmol TE/g). Methanol-water mixtures, particularly in the 40:10 ratio, also exhibited high activity (928.675 µmol TE/g). Acetone extracts and their mixtures with water had somewhat lower values, while water-based extracts showed the lowest antioxidant activity (192.9 µmol TE/g). Conclusion: These results indicate a significant potential of solvent mixtures, particularly acetone-water mixtures, in enhancing bioactivity and antioxidant effects.

Accurate reconstruction of latent environmental fields from sparse and indirect observations is a foundational challenge across scientific domains-from atmospheric science and geophysics to public health and aerospace safety. Traditional approaches rely on physics-based simulators or dense sensor networks, both constrained by high computational cost, latency, or limited spatial coverage. We present the Temporal Radiation Operator Network (TRON), a spatiotemporal neural operator architecture designed to infer continuous global scalar fields from sequences of sparse, non-uniform proxy measurements. Unlike recent forecasting models that operate on dense, gridded inputs to predict future states, TRON addresses a more ill-posed inverse problem: reconstructing the current global field from sparse, temporally evolving sensor sequences, without access to future observations or dense labels. Demonstrated on global cosmic radiation dose reconstruction, TRON is trained on 22 years of simulation data and generalizes across 65,341 spatial locations, 8,400 days, and sequence lengths from 7 to 90 days. It achieves sub-second inference with relative L2 errors below 0.1%, representing a>58,000X speedup over Monte Carlo-based estimators. Though evaluated in the context of cosmic radiation, TRON offers a domain-agnostic framework for scientific field reconstruction from sparse data, with applications in atmospheric modeling, geophysical hazard monitoring, and real-time environmental risk forecasting.

We investigate the phenomenology of a model in which the proton is rendered absolutely stable by an IR mechanism that remains robust against unknown quantum gravity effects. A linear combination of baryon number and lepton flavors is gauged and spontaneously broken to a residual $\mathbb{Z}_9$ discrete gauge symmetry enforcing a strict selection rule: $\Delta B = 0\,(\mathrm{mod}\,3)$. Despite its minimal field content, the model successfully accounts for established empirical evidence of physics beyond the SM. High-scale symmetry breaking simultaneously provides a seesaw mechanism explaining the smallness of neutrino masses, minimal thermal leptogenesis, and a viable phenomenology of the majoron as dark matter. Any cosmic string-wall network remaining after inflation is unstable for numerous charge assignments. Lepton flavor non-universality, central to the construction, leads to predictive neutrino textures testable via oscillation experiments, neutrinoless double beta decay, and cosmology. The model motivates searches in $X$- and $\gamma$-ray lines, neutrino telescopes, and predicts CMB imprints.

In the hilly and mountainous area of Republic of Srpska natural grasslands (meadows and pastures) represent significant resource for grazing and production of bulky livestock food. However, in addition to the big importance and available areas, the production of bulky fodder on natural grasslands are relatively low. Limiting production factors of feed in mountainous areas are the quality of the soil and the climatic conditions. Low yields of hay of natural grassland can be improved by application mineral fertilizers. In addition to the application of mineral fertilizers, which should be one from implementation of basic agrotechnical measures more profitable plant-based, ultimately and animal production it is necessary to apply appropriate quantities of fertilizers at the most suitable time of growing season herbal type. The goal of this research was to determine the influence of different amounts of nitrogen on productivity of natural grassland type Agrostietum vulgaris on low available phosphorus and potassium soil. This study was carried out in two seasons (2018 and 2019). The application of nitrogen had a positive impact on grassland productivity. The highest average green forage yield of 13.15 t ha-1 and hay yield of 3.48 t ha-1 was achieved with the application of 94.5 kg ha-1 of nitrogen, and the lowest was achieved in control without fertilization. The average increase in hay yield in the first year was 37.6% and in the second year it was 5.6% higher than in the first year. The application of mineral fertilizers on natural grasslands on low phosphorus and potassium soil is of crucial importance for obtaining higher yields of green forage and hay.

Climate change has significantly altered weather patterns, increasing the frequency and intensity of drought events and posing serious challenges to agricultural production, particularly fruits. Water scarcity and increased evapotranspiration demands, posing critical challenges to global agriculture and threatening the sustainability of fruit production. Understanding the response of fruit crops to drought stress and their specific irrigation needs is essential for developing resilient and sustainable cultivation systems. This work aims to consolidate existing research and provide a comprehensive analysis of strategies to mitigate the impacts of water scarcity on fruit crops. The paper focuses on the following key areas: (1) evaluating the growth and performance of fruit crops across diverse environments and cultivation methods; (2) assessing the water needs of fruit crops, including evapotranspiration rates, crop coefficients, and strategies for efficient water use; (3) identifying and recommending the most effective irrigation methods; (4) exploring advanced tools for real-time monitoring of plant water status; and (5) comparing and evaluating existing models for quantifying plant water requirements under drought conditions, with an emphasis on their potential integration into decision support systems (DSS). By addressing these critical aspects, it aims to provide actionable insights and foster the adoption of innovative irrigation and water management strategies to support sustainable fruit crop production in the context of climate change.

This cross-sectional study investigates the global burden of nontraumatic subarachnoid hemorrhage in 2021.

We investigate the phenomenology of a model [1] in which the proton is rendered absolutely stable by an IR mechanism that remains robust against unknown quantum gravity effects. A linear combination of baryon number and lepton flavors is gauged and spontaneously broken to a residual ℤ9 discrete gauge symmetry enforcing a strict selection rule: ΔB = 0 (mod 3). Despite its minimal field content, the model successfully accounts for established empirical evidence of physics beyond the SM. High-scale symmetry breaking simultaneously provides a seesaw mechanism explaining the smallness of neutrino masses, minimal thermal leptogenesis, and a viable phenomenology of the majoron as dark matter. Any cosmic string-wall network remaining after inflation is unstable for numerous charge assignments. Lepton flavor non-universality, central to the construction, leads to predictive neutrino textures testable via oscillation experiments, neutrinoless double beta decay, and cosmology. The model motivates searches in X- and γ-ray lines, neutrino telescopes, and predicts CMB imprints.

Maize is the most widely cultivated crop on arable land in Bosnia and Herzegovina. Yields are quite inconsistent due to several factors, with one of the most significant being the lack of moisture during the growing season, particularly during the pollination period. Irrigation is a measure taken to mitigate the harmful effects of drought. A maize field trial was conducted over two growing seasons (2022/2023) with three replications. The local hybrid BL-43 was sown in three irrigation treatments and two fertilization variants. During the season, morphometric parameters of maize plants were measured. Statistically highly significant differences were observed between yields and yield components. The greatest differences were found in plant height among the irrigation treatments, as well as between the two years of study. Maize yield showed high variability under the influence of the applied treatments. The highest yield (11,031 kg ha-¹) was achieved with the 100% irrigation treatment combined with a higher rate of mineral fertilizer. Irrigation treatment had a much greater effect on yield components and total maize yield than fertilization. Applying irrigation at 50% and 100% of the required norm increased the values of yield components and overall maize yield in 2023 by about 27%. In the drought year (2022), the increase was 27% with 50% irrigation and 37% with 100% irrigation. In the dry year of 2022, when total precipitation was 35% lower compared to the multi-year average, irrigation had a stronger effect on maize yield components. Besides the irrigation, further research should consider the improvement of soil organic matter content and soil health as tools for improved drought resistance.

The authors used a quantitative research method to analyze the market trends of fresh plums in Serbia. For this purpose, they used competitiveness parameters that were processed using standard descriptive statistics tools. The goal was to review the foreign trade of plums, as well as to determine the trend of competitiveness indicators for this fruit. The results show that during the analyzed ten-year period from 2014 to 2023, there was a slight downward trend in all production parameters of this fruit, but that Serbia was self-sufficient in its production, as well as price-competitive on the world market. Also, a downward trend in certain competitiveness indicators was observed, which indicates a further strengthening of the market position of this fruit species. Further research should be focused on determining the causes of the trend in competitiveness indicators, as well as ways to strengthen them.

Background/Objectives: Improper use of systemic antibiotics remains a significant concern in hospital settings, contributing to increased antimicrobial resistance and suboptimal clinical outcomes. The COVID-19 pandemic exacerbated this issue. This study aimed to evaluate long-term trends in antibiotic utilization in low-resource settings at a tertiary care teaching hospital, focusing specifically on the changes before, during, and after the COVID-19 pandemic. Methods: This retrospective observational study analyzed antibiotic utilization data from the University Clinical Centre of the Republic of Srpska over ten years (2015–2024). Antibiotic consumption was expressed in defined daily doses (DDD) per 100 bed-days, and compared across three periods: pre-COVID-19 (2015–2019), COVID-19 (2020–2022), and post-COVID-19 (2023–2024). Additionally, antibiotic use was categorized according to the WHO AWaRe classification. Results: Antibiotic utilization peaked during the COVID-19 period, with the highest rate observed in 2021 (91.5 DDD/100 bed-days), despite a decrease in hospital admissions. The most frequently used antibiotics were cephalosporins, penicillins, and metronidazole. A significant increase in the use of azithromycin, meropenem, piperacillin/tazobactam, vancomycin, and colistin was noted during the COVID-19 and post-COVID-19 periods (p < 0.05), along with a notable decline in penicillin use. Watch and Reserve antibiotic use rose significantly (p < 0.05), while Access group use fell from 67% to 49.2%. Conclusions: These findings underscore the lasting impact of the COVID-19 pandemic on antibiotic prescribing patterns and emphasize the urgent need for strengthened antimicrobial stewardship efforts to ensure rational antibiotic use and combat antimicrobial resistance.

Parallel robots offer high precision, stiffness, and dynamic performance, but their nonlinear and coupled dynamics pose challenges for real-time trajectory tracking. This paper presents a hybrid control framework that combines joint-space and task-space controllers to simultaneously manage actuator dynamics and end-effector motion. By leveraging both control domains, the proposed approach addresses the limitations of single-space strategies. Stability is established via Lyapunov analysis, and experimental results confirm superior tracking accuracy compared to conventional acceleration-based controllers, demonstrating effectiveness for high-precision, dynamic applications.

Tumor-infiltrating lymphocytes (TILs) are a diverse population of immune cells that play a central role in tumor immunity and have emerged as critical mediators in cancer immunotherapy. This review explores the phenotypic and functional diversity of TILs—including CD8+ cytotoxic T cells, CD4+ helper T cells, regulatory T cells, B cells, and natural killer (NK) cells—and their dynamic interactions within the tumor microenvironment (TME). While TILs can drive tumor regression, their activity is often hindered by immune checkpoint signaling, metabolic exhaustion, and stromal exclusion. We highlight TIL recruitment, activation, and polarization mechanisms, focusing on chemokine gradients, endothelial adhesion molecules, and dendritic cell-mediated priming. Special emphasis is placed on preclinical models that evaluate TIL function, including 3D tumor spheroids, organoid co-cultures, syngeneic mouse models, and humanized systems. These provide valuable platforms for optimizing TIL-based therapies. Furthermore, we examine the prognostic and predictive value of TILs across cancer types, their role in adoptive cell therapy, and the challenges of translating preclinical success into clinical efficacy. Emerging technologies such as single-cell sequencing, neoantigen prediction, and biomaterial platforms are transforming our understanding of TIL biology and enhancing their therapeutic potential. Innovative strategies—ranging from genetic engineering and combination therapies to targeted modulation of the TME—are being developed to overcome resistance mechanisms and improve TIL persistence, infiltration, and cytotoxicity. This review integrates current advances in TIL research and therapy, offering a comprehensive foundation for future clinical translation. TILs hold significant promise as both biomarkers and therapeutic agents, and with continued innovation, they are poised to become a cornerstone of personalized cancer immunotherapy.

In this study, a greenhouse experiment was carried out from April to July 2024 to assess the effectiveness of four ornamental plants in removing heavy metals from the polluted soil surrounding the Zenica steel mill in Bosnia and Herzegovina. The selected ornamental plants - blue mink (Ageratum houstonianum Mill.), marigold (Tagetes erecta L.), impatiens (Impatiens walleriana Hook. f.), and begonia (Begonia semperflorens - Cultorum Group) - demonstrated potential for addressing soil contamination. These plants were cultivated in grow bags filled with soil collected from different areas surrounding the Zenica steel mill. The concentrations of heavy metals (Cu, Zn, Pb, Cd, Cr, Mn, and Fe) in both soil and plant samples were analyzed using atomic absorption spectrophotometry. The findings of this study reveal that soils adjacent to the Zenica steel mill are heavilycontaminated with Zn, Cd, and Pb and also contain notable levels of Mn and Fe. The bioaccumulation factor (BAF) and translocation factor (TF) were calculated to determine the potential of the selected ornamental plants to uptake and transport heavy metals from the soil to its aboveground parts. The BAF values for all heavy metals in all studied plant species were consistently below 1, indicating a limited capacity to remove heavy metals from the soil. This limited effectiveness can be attributed, among other factors, to the high pH levels of the tested soils. Despite the limitation, the findings revealed a significant difference in the plants’ capacity to uptake and accumulate heavy metal ions from the examined soils. Among the tested plants, blue mink demonstrated the highest ability to absorb Cu, Pb, Cr and Fe, while the highest concentrations of Zn and Cd were found in begonia

We demonstrate non-immunogenic circRNA as a tool for targeted gene regulation in plants, where it acts in an isoform- and sequence-specific manner, enabling future agronomic applications. Circular RNAs (circRNAs) are single-stranded RNA molecules characterized by their covalently closed structure and are emerging as key regulators of cellular processes in mammals, including gene expression, protein function and immune responses. Recent evidence suggests that circRNAs also play significant roles in plants, influencing development, nutrition, biotic stress resistance, and abiotic stress tolerance. However, the potential of circRNAs to modulate target protein abundance in plants remains largely unexplored. In this study, we investigated the potential of designer circRNAs to modulate target protein abundance in plants using Arabidopsis protoplasts as a model system. We show that PEG-mediated transfection with a 50-nt circRNAGFP containing a 30-nt GFP-antisense sequence results in a dose- and sequence-dependent reduction of GFP reporter target protein abundance. Notably, a single-stranded open isoform of circRNAGFP had little effect on protein abundance, indicating the importance of the closed circular structure. Additionally, circRNAGFP also reduced GFP abundance in Arabidopsis mutants defective in RNA interference (RNAi), suggesting that circRNA activity is independent of the RNAi pathway. We also show that circRNA, unlike dsRNA, does not induce pattern-triggered immunity (PTI) in plants. Findings of this proof-of-principle study together are crucial first steps in understanding the potential of circRNAs as versatile tools for modulating gene expression and offer exciting prospects for their application in agronomy, particularly for enhancing crop traits through metabolic pathway manipulation.