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Xinyi Lin, Xinhe Zhang, Zheliang Wang, Juntao Chen, Jaeyong Lee, Ariel J. Lee, Hang Yang, Antoine Remy et al.

Melisa Oraščanin, M. Bektašević, E. Šertović, Milica Cvijetić, Ivana Flanjak, Vildana Alibabić

With the discovery of the main bioactive compounds, royal jelly (RJ) takes a significant role in the food and pharmaceu-tical industry. One of the most important ingredients of RJ is 10-hydroxy-2-decenoic acid (10-HDA). In this paper, ten samples of RJ were analyzed, which were collected from the area of northwestern Bosnia and Herzegovina. In addition to 10-HDA, glucose, fructose, sucrose, and maltose content, physicochemical parameters were analyzed: pH value, total acidity, water content, protein content, and antioxidant activity of RJ. The obtained results show that samples of RJ meet international standards with regard to the content of 10-HDA. Considering the established quality and very high antioxi-dant activity of the analyzed samples (analyzed with DPPH and FRAP methods) they have significant potential in devel-opment of functional products with pronounced nutritional and biological capacity. This work is first attempt in estab-lishment of RJ quality criteria in this area.

K. Lim, Z. Tippu, P.G. Corrie, M. Hubank, J. Larkin, T. Lawley, M. Stares, Grant D. Stewart et al.

Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.

Jasmin Katica, T. Goletić, Aida Kavazović, Maja Varatanović, Ć. Crnkić

This study aims to estimate the number of AMY2B gene copies and measure serum amylase activity in several Balkan dog breeds. Additionally, it explores the relationship between these genetic and biochemical parameters. Blood samples from 85 dogs representing eight breeds were collected, DNA was extracted, and AMY2B copy numbers were determined using droplet digital PCR. AMY2B gene copies ranged from 7.7 to 18.4, with a mean of 12.4 ± 2.2. Significant breed-related differences were observed (p = 0.025), with Istrian Wire-Haired Hounds showing the highest mean copy number (13.9 ± 1.5) and Posavatz Hounds the lowest (10.8 ± 1.5). Serum amylase activity ranged from 3.3 to 17.8 µkat/L, with a mean of 8.7 ± 2.6, and showed significant interbreed differences (p = 0.004), with Barak breed displaying the highest activity. Serum glucose levels varied widely, but no significant interbreed differences were detected (p = 0.340). No significant correlation was found between AMY2B copy numbers and serum amylase activity or glucose levels. The study concludes that Balkan dogs have AMY2B copy numbers similar to other European breeds, likely reflecting historical agricultural practices in the region, thereby facilitating better starch digestion. While significant variations exist among breeds, the lack of correlation between gene copy number and amylase activity suggests that other factors influence enzyme levels.

Marta Narigina, Agris Vindecs, Dušanka Bošković, Y. Merkuryev, A. Romānovs

This study introduces an AI-based framework for stroke diagnosis that merges clinical data and curated imaging data. The system utilizes traditional machine learning and advanced deep learning techniques to tackle dataset imbalances and variability in stroke presentations. Our approach involves rigorous data preprocessing, feature engineering, and ensemble techniques to optimize the predictive performance. Comprehensive evaluations demonstrate that gradient-boosted models outperform in accuracy, while CNNs enhance stroke detection rates. Calibration and threshold optimization are utilized to align predictions with clinical requirements, ensuring diagnostic reliability. This multi-modal framework highlights the capacity of AI to accelerate stroke diagnosis and aid clinical decision making, ultimately enhancing patient outcomes in critical care.

José Daniel Langendorf da Silva, Namir Halilović, Valdir Florêncio da Veiga Junior, Rodrigo Leonard Barbosa Rodrigues, F. Peixoto

This work developed and evaluated a rapid, cost‐effective, and mobile analytical method for the quantification of stabilizers in nitrocellulose‐based propellants, using thin‐layer chromatography and image densitometry. The method demonstrated effectiveness in the separation and quantification of diphenylamine and N‐nitrosodiphenylamine, showing linearity, accuracy, and precision for concentrations above 0.3 wt%. To address limitations at low concentrations, a screening test approach with a cutoff value of 0.3 wt% was proposed. Innovations included a custom‐built dark chamber to improve photographic records, and a custom script for automated image analysis, using open‐source software. The developed analytical procedure, along with the supporting tools created, offers a promising solution for rapid and efficient field monitoring of nitrocellulose‐based propellant stability, with the potential to complement existing laboratory methods in ammunition surveillance.

Imana Sokolovic Tahtovic, S. Sokolovic

Objective: Obesity and overweight represent a global public health crisis, due to the increased risk of cardiovascular diseases consequent to many factors such as metabolic dysregulation and chronic inflammation. This study aimed to compare the Heart Rate variability (HRV) between obese and non-obese hypertensive patients. Design and method: A cross-sectional study included 76 hypertensive patients, referred to the Functional Explorations department. Anthropometric and clinical data were collected. All patients underwent 24-hour Ambulatory Blood Pressure (BP) Monitoring. HRVs were measured (standard deviation in percentage) during 24-hour, diurnal and nocturnal periods. Patients were divided into two groups, according to their body mass index (BMI, whether < 30 kg/m 2 or = 30 30 kg/m 2 and more): G1 (obese, n=39) and G2 (non-obese, n=37). Results: Mean age was 55±10 vs. 52±15 years and mean BMI was 34±4 vs. 26±2 kg/m 2 in G1 and G2, respectively. Both groups were matched for sex (66.7% of females in G1 vs. 48.6% of females in G2) and comorbidities (mainly diabetes and dyslipidemia), but G1 included a higher proportion of metabolic syndrome (p<0.05). Mean values of 24-hour Systolic and Diastolic BPs were 136±10 mmHg vs. 130±11 mmHg (p=0.022), and 84±9 mmHg vs. 80±9 mmHg (p=0.066), respectively in G1 and in G2. Mean values of 24-hour, diurnal and nocturnal HRVs were 14±3% vs. 16±3%; 14±3% vs. 16±3%; 7±3% vs. 9±6%, respectively in G1 and in G2. Diurnal and 24-hour HRVs were statistically lower in G1 (p=0.010 and 0.035, respectively). However, no significant difference was observed in nocturnal HRV (p=0.279) between the two groups. Conclusions: This study revealed lower HRVs among obese patients which highlights a clear association between obesity and reduced autonomic nervous system function, particularly with diminished parasympathetic activity. This HRV reduction, resulting in an imbalance in autonomic regulation, increases cardiovascular risk. Managing weight seems to be the key to minimize these negative impacts.

K. Sweerts, Stefan Calder, G. O’Grady, C. Varghese, Philip G. Dinning, Daan H C A Bosch, Z. Mujagic, J. Conchillo et al.

Elmedina Mrkulić, Jasmina Mahmutović, Sabina Terzic

Background: Health-related quality of life (HRQoL) evaluates the impact of health conditions on personal functioning. Type 1 diabetes mellitus (T1DM) in children and adolescents can significantly affect HRQoL due to the demands of daily disease management, psychological burden, and potential complications. The use of validated tools like Pediatric Quality of Life Inventory (PedsQL™) questionnaires is essential in assessing HRQoL. Combining generic and disease-specific scales offers a comprehensive evaluation. Aim: The aim of this study is to assess the extent to which the PedsQL 4.0 and PedsQL 3.0 questionnaires explain the overall quality of life of children and adolescents with type 1 diabetes when used separately and in combination. Additionally, the study aims to identify which specific domains within these questionnaires are most significant in explaining the variability in overall quality of life scores. Methods: A cross-sectional descriptive-analytical study was conducted from October 2021 to February 2022. The study assessed the quality of life of 50 children and adolescents (aged five to 18 years) diagnosed with type 1 diabetes mellitus, residing in Sarajevo Canton. Of these, 47 children/adolescents provided self-reports, while three children aged five to seven years were excluded from self-report analyses due to developmental limitations. However, parent proxy-reports were obtained for all 50 participants, including the three younger children. Accordingly, the final analysis included 47 child/adolescent self-reports and 50 parent proxy-reports. The study included children with a disease duration of >6 months and parental consent. The PedsQL™ 4.0 and PedsQL™ 3.0 Diabetes Module were used. Data analysis was performed using Statistical Package for Social Sciences (SPSS) version 26 (IBM Corp., Armonk, New York), including reliability testing, descriptive statistics, and multiple linear regression. Linear regression was selected to quantify the contribution of each questionnaire domain to overall HRQoL, offering an interpretable and robust method for assessing additive domain effects. Results: The combined use of generic and diabetes-specific measures provided the most accurate assessment of HRQoL, capturing both general well-being and disease-specific challenges. Diabetes symptoms and physical functioning were key explainors. Conclusion: The combined use of generic and diabetes-specific tools enables a more nuanced and comprehensive assessment of HRQoL in children and adolescents with T1DM. This study demonstrates that neither tool alone offers sufficient coverage, reinforcing the necessity of integrated assessment.

S. Assmann, Bjorn Winkens, Andrea Bours, Brigitte A. B. Essers, Tze Lam, Z. Mujagic, S. O. Breukink, D. Keszthelyi

Alan Maksimović, Selma Filipović, Muamer Obhođaš, Bianca Pehar, Nermina Spahija, Kenan Tabaković, Alma Šeho-Alić, Jovana Dervovic et al.

Background: Hepatobiliary tumors are uncommon in dogs, and metastatic liver tumors are diagnosed more frequently than primary liver tumors. Hepatocellular carcinoma is the most prevalent primary liver malignant tumor. Case Description: An 11-year-old spayed female Tibetan Terrier was referred to the University of Sarajevo Veterinary Teaching Hospital due to recurrent painful urination attempts, straining urination, hematuria, and decreased appetite. Abdominal ultrasonography revealed a moderately distended bladder containing urolith, bladder wall thickening, and sediment. Incidentally, a hyperechoic hepatic mass on the left medial liver lobe and hepatomegaly were detected along with gallbladder sludge. Surgical cystolithotomy and partial liver lobectomy were performed. Histopathological examination confirmed the hepatic mass as clear cell hepatocellular carcinoma (CCHCC). Conclusion: Although this rare histological subtype has been documented, its biological behavior and clinical features remain poorly understood due to the scarcity of cases. A recent publication by Jung et al. (2021). described the first cytological, histological, and clinical case presentation of CCHCC in dogs, suggesting that obesity and hyperlipidemia may be potential risk factors. However, these proposed risk factors were not detected in the present case, implying that CCHCC in dogs is a rare and poorly understood condition that warrants further attention in veterinary research.

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