Background: Thyroid cancer (TC) is the most common endocrine malignancy and is generally associated with a favorable prognosis. Its incidence has increased worldwide, whereas epidemiological data from Bosnia and Herzegovina, particularly Tuzla Canton, remain limited. Aim: The aim of this study is to determine the incidence, five-year period prevalence, histological distribution, and basic demographic characteristics of TC in Tuzla Canton between 2020 and 2024. Study design: This is a retrospective descriptive observational study. Methods: Records of 483 patients evaluated by the Council for Benign and Malignant Thyroid Diseases at the University Clinical Center Tuzla between January 1, 2020, and December 31, 2024, were retrospectively reviewed. Patients were included if they had histopathologically confirmed TC, were aged ≥15 years, and resided in Tuzla Canton. Incidence and five-year period prevalence were calculated using the latest available population estimates. Results: Of the 483 evaluated patients, 142 met the inclusion criteria. The cohort included 108 women (76%) and 34 men (24%), corresponding to a female-to-male ratio of 3.18:1. The median age at diagnosis was 56 years. Papillary TC was the most common type (n=105; 74%), followed by follicular (n=18; 13%), medullary (n=15; 10%), and anaplastic (n=4; 3%). The age-standardized average annual incidence was 6.99 per 100,000 population, while the five-year period prevalence was 32.98 per 100,000. Incidence was higher among women than among men and increased during the study period. The highest age-specific incidence was observed among women aged ≥75 years and men aged 65-74 years. Three deaths occurred during follow-up, of which two were directly attributable to TC; both TC-related deaths occurred in patients with anaplastic carcinoma. Conclusion: TC incidence in Tuzla Canton was lower than reported global and European estimates but increased during the five-year study period. Papillary carcinoma predominated, particularly among women. Longer-term population-based studies and the establishment of a national thyroid cancer registry are needed to improve epidemiological surveillance in Bosnia and Herzegovina.

Sex estimation is a fundamental component of biological profiling in forensic anthropology, particularly when skeletal remains are incomplete or fragmented. This study aimed to evaluate sex estimation of the cranial base using geometric morphometrics and to assess the predictive value of cranial base morphology for sex estimation. The study included 211 adult skulls (139 male, 72 female) from the Bosnian population. Each skull was digitized to generate 3D models, and 27 anatomical landmarks were recorded. Landmark coordinates were standardized using Generalized Procrustes Analysis, Principal Component Analysis, Discriminant Function Analysis with permutation testing, and regression of shape on centroid size. Statistically significant sex estimation was observed at both the form (shape and size) and shape levels. Classification accuracy based on cranial base form reached 92.81% for males and 86.11% for females. Shape-based classification, after removal of size effects, also showed high accuracy (90.65% for males and 81.94% for females). Regression analysis indicated that size contributed significantly but modestly to shape variation. The cranial base exhibits stable sexually dimorphic patterns and may represent a reliable anatomical region for sex estimation. These findings contribute to population-specific standards for the Bosnia and Herzegovina population and support the forensic applicability of 3D geometric morphometric approaches.

Background: The Health in All Policies (HiAP) approach promotes the systematic integration of health considerations into policymaking across non-health sectors to address social determinants of health and improve population health outcomes. Although increasingly recognized internationally, the extent of its legislative implementation in the Republic of Srpska remains unclear. Objective: To assess the extent to which HiAP principles are embedded in sectoral legislation in the Republic of Srpska and to identify strengths and gaps in current legal frameworks. Methods: A structured content analysis of the text of laws was conducted across ten priority sectors. Twenty-two laws were reviewed using an analytical framework based on five core HiAP components: health outcomes, intersectoral governance, health equity, evidence-informed policymaking, and monitoring and accountability. The presence and distribution of these components were systematically examined across sectors. Results: Health considerations were frequently reflected in the text of the analysed legislation. Explicit references to health outcomes and intersectoral governance were identified in more than 60% of laws. However, integration was uneven across sectors. Health equity principles were inconsistently incorporated, while monitoring, evaluation, and accountability mechanisms were insufficiently developed, with explicit provisions found in fewer than half of the laws. No analysed law formally mandated Health Impact Assessment as a policy instrument. Conclusions: The Republic of Srpska has an existing legislative basis for advancing HiAP, but implementation remains fragmented rather than systematic. Addressing identified gaps—particularly in health equity, Health Impact Assessment, and health-oriented monitoring mechanisms—through targeted legislative reforms could improve policy coherence, accountability, and long-term sustainability. To our knowledge, this is the first systematic content analysis of HiAP integration in the sectoral legislation of the Republic of Srpska; it applies a replicable analytical framework derived from the WHO HiAP Framework for Country Action that is transferable to other decentralised and transitional governance settings.

Background/Objectives: Antipsychotic drug utilization has changed substantially over recent decades, reflecting evolving prescribing practices, drug availability, and treatment guidelines. Methods: This study analyzed national antipsychotic consumption in Serbia from 2006 to 2024 using official data from the Medicines and Medical Devices Agency of Serbia. Utilization was expressed as defined daily doses per 1000 inhabitants per day, and trends were assessed using linear and joinpoint regression analyses. Results: Total antipsychotic utilization increased from 4.35 to 14.42 DDD/1000 inhabitants/day, representing a 231.5% increase. This growth was predominantly driven by atypical antipsychotics, whose utilization increased from 1.16 to 10.91 DDD/1000 inhabitants/day (+840.2%). In contrast, typical antipsychotic utilization remained relatively stable in absolute terms. The share of atypical antipsychotics increased from 26.7% in 2006 to 75.6% in 2024, while the atypical: typical utilization ratio increased from 0.36 to 3.10. Atypical antipsychotics surpassed typical agents in 2013. Marked increases were observed for olanzapine, quetiapine, aripiprazole, paliperidone, risperidone, and clozapine, while chlorpromazine and fluphenazine declined. Conclusions: These findings demonstrate a substantial increase in overall antipsychotic utilization in Serbia and a pronounced structural shift toward atypical agents, highlighting the need for continued monitoring of prescribing trends, safety outcomes, and population-level treatment patterns.

Background/Objectives: Bilateral thoracoscopic sympathectomy (BTS) is the definitive treatment for primary focal hyperhidrosis, yet postoperative pain remains an undertreated consequence with no established analgesic consensus. This study compared three analgesic regimens on pain trajectory, opioid consumption, and functional recovery following BTS. Methods: In this prospective observational cohort study, 300 patients undergoing BTS were allocated in a non-randomized manner reflecting institutional practice to three parallel cohorts (n = 100 each): Group 1 received systemic opioids alone; Group 2 received opioids plus pre-emptive local anesthetic wound infiltration; and Group 3 received opioids plus thoracoscopic-guided intercostal nerve block (ICNB). Primary outcomes included pain intensity on the Numerical Rating Scale and total opioid consumption. Results: ICNB patients reported significantly lower mean peak pain scores (3.8 ± 1.7) versus local infiltration (4.6 ± 1.9) and opioid-only groups (5.2 ± 2.1; p < 0.001). Total opioid consumption was reduced by 38% in the ICNB group (12.4 ± 4.8 mg vs. 20.1 ± 6.3 mg; p < 0.001). Moderate-to-severe pain occurred in 42.0% of ICNB patients versus 74.0% of controls (p < 0.001). ICNB was independently associated with reduced moderate-to-severe pain (adjusted odds ratio (AOR) 0.31; 95% confidence interval (CI) 0.17–0.56; p < 0.001). ICNB patients returned to normal activities faster (median 3 vs. 5 days; p = 0.008) with higher satisfaction (91.0% vs. 78.0%; p = 0.044). Conclusions: In this observational cohort, ICNB was associated with significantly lower postoperative pain scores, reduced opioid consumption, and faster functional recovery following BTS. These findings suggest that ICNB may be an effective adjunct analgesic strategy for ambulatory BTS, pending confirmation in randomized controlled trials.

Successful speech communication in multi-talker scenarios requires a skillful combination of sustained attention and rapid attention switching. While the neurophysiology literature offers detailed insights into the neural underpinnings of sustained attention, there remains considerable uncertainty on how attention switching takes place. In this study, using EEG recordings from normal-hearing adults in an immersive multi-talker environment, we measured the neural encoding of two competing speech streams amid background babble. Participants were cued to switch attention between streams every 15–30 s. Neural tracking was assessed via Temporal Response Functions (TRF), confirming reliable decoding of attentional focus. Our results indicate asymmetric disengagement and engagement processes during attention switches, where the neural tracking of the new target stream emerges before disengaging from the previous target, revealing a transient simultaneous encoding of two speech streams. That transition was closely mirrored by a reduction in EEG alpha power, informing on the cognitive effort during different phases of the attention switch. We then isolated cortical activity reflecting lexical prediction mechanisms to determine how lexical context is updated after an attention switch, comparing four context-accumulation strategies that were constructed using Large Language Models. Our findings elucidate both the temporal and contextual mechanisms underlying auditory attention shifts, pointing to the possibility that listeners carry out a reset in lexical context after switching attention. By focusing on dynamic attentional reallocation, this study offers insights into the brain’s capacity for flexible speech processing in complex listening environments.

Cationic surfactants are widely used in disinfectants, creating a need for rapid and reliable analytical methods for their determination in complex formulations. In this study, a new hydrophobic ion-pair, 1,3-didecyl-2-methylimidazolium tetrakis(perfluorophenyl)borate (DDMIm–TPFPhB), was developed and applied as an ionophore in a potentiometric sensor. The ion-pair was incorporated into a PVC membrane and evaluated by direct potentiometric measurements and titrations. The sensor exhibited near-Nernstian responses toward selected cationic surfactants (56.8–59.1 mV per decade), low detection limits (1.4–2.2 × 10−6 M), and stable signal behavior, along with good selectivity and stability over a pH range of 3–9. Application on commercial disinfectant samples showed good agreement with a commercial ion-selective electrode. According to the charge decomposition analysis performed using density functional theory calculations, the number of electrons donated from perfluorotetraphenyl borate to 1,3-didecyl-2-methylimidazolium is 0.25 e. In contrast, the back-donation from the cation to the anion is only 0.05 e, indicating a relatively substantial overall charge transfer of 0.20 e. This pronounced charge transfer, together with dominant dispersion interactions, contributes to enhanced ion-pair stability within the membrane phase, which is reflected in reduced signal drift and improved analytical performance. These findings establish a direct link between molecular-level interactions and sensor behavior, providing a rational basis for the design of potentiometric sensors for real-sample analysis.

Background Glioblastoma (GBM) invasion is clinically decisive but difficult to model systematically. Existing patient-derived xenograft (PDX) resources rarely couple reproducible in vivo invasion phenotypes with matched multi-omic profiles at scale, limiting mechanistic insight and phenotype-informed therapeutic hypotheses. Methods We established the HGCC Phenobank, comprising 65 patient-derived GBM stem-like cultures with matched multi-omic profiling and orthotopic engraftment in 449 mice. Blinded histopathology quantified ten invasion traits per case. These phenotypes were integrated with RNA sequencing, DNA methylation, and mass-spectrometry-based proteomics. Multi-Omic Factor Analysis (MOFA) identified latent molecular programs. Phenotype-specific RNA signatures were matched to LINCS drug-perturbation profiles and validated in 3D gliomasphere and ex vivo brain-slice assays. Results Two dominant, reproducible invasion modes emerged across models: diffuse parenchymal infiltration and perivascular/condensed growth. Proneural cultures formed more aggressive tumors in immunodeficient mice, and mouse survival showed a modest correlation with patient survival in matched cases (Pearson 0.1832, 0.045). MOFA identified 15 latent factors; Factor 1, enriched for ASCL1/OLIG1/OLIG2 programs and associated with TP53/DCHS2/WNK2 alterations, was linked to increased tumor formation, diffuse invasion, and shorter mouse survival, and stratified GBM patients in TCGA and in our matched patient cohort. Drug-signature matching separated mechanisms targeting diffuse versus perivascular invasion. Experimental validation confirmed phenotype-selective sensitivities, and inhibitors PIK-75 and buparlisib suppressed invasion dynamics across representative models in 3D and brain-slice assays. Conclusions The HGCC Phenobank provides the first openly available PDX resource that systematically links GBM invasion phenotypes to multi-omic programs and therapeutic predictions. This framework enables reproducible model selection, mechanistic dissection of invasion modes, and phenotype-guided therapeutic discovery. Key Points Diffuse and perivascular invasion define orthogonal GBM axes ASCL1/OLIG factor links initiation, diffuse growth, and survival Phenotype-matched drugs validated; PIK-75 and buparlisib curb invasion dynamics Importance of the Study Glioblastoma invasion varies substantially between patients, yet existing patient-derived xenograft resources rarely combine reproducible in vivo phenotyping with matched multi-omic profiling at scale. The HGCC Phenobank addresses this gap with standardized, blinded scoring of ten invasion traits across 449 orthotopic xenografts from 65 molecularly characterized GBM stem-like cultures, integrated with transcriptomic, methylomic, and proteomic data. We identify two dominant, reproducible invasion modes and a cross-modal neurodevelopmental program, the ASCL1/OLIG1/2-associated Factor 1, that links tumor initiation, diffuse growth, and survival in mice, and stratifies GBM patients in TCGA and in our matched patient cohort. In a spatially resolved xenograft section, Factor 1 signal localizes to the invasive tumor periphery. By matching phenotype-specific RNA signatures to drug-induced transcriptional responses, we show that invasion phenotypes nominate selective vulnerabilities, exemplified by PIK-75. This openly shared resource enables reproducible model selection, mechanistic dissection of invasion programs, and phenotype-guided therapeutic discovery.

The β-catenin destruction complex (BDC) regulates WNT–β-catenin signaling and is a prime therapeutic target in colorectal cancer, yet its biochemical complexity has hindered mechanistic understanding. We mapped the sequence–function landscape of the BDC using tiled base editor screens across its components CTNNB1, AXIN1, APC and GSK3B. Amongst ~150 previously unreported mutations that affected WNT signaling, we discovered gain-of-function and separation-of-function alleles that reveal mechanisms of complex assembly, including a β-catenin region regulating TCF/LEF transcription factor binding. Critically, we found that the AXIN1–β-catenin interface controls signaling flux through the oncogenic BDC found in APC-mutant cancers. In cells expressing truncated APC, β-catenin itself scaffolds BDC assembly, establishing a substrate-assisted autoregulatory mechanism. This architecture represents an unexploited therapeutic vulnerability: strengthening the AXIN1–β-catenin interaction restores destruction complex function and impairs the growth of colorectal cancer cells. Our mutational resource provides a foundation for mechanistic understanding and therapeutic targeting of the WNT pathway. Base-editing mutagenesis reveals that autoregulation of beta-catenin drives optimal (or ‘just right’) oncogenic WNT signaling in cancer.

Background: Bartonella henselae infection has been associated with a broad spectrum of neurological and autonomic manifestations, although its impact on autonomic nervous system function remains insufficiently characterized, and the aim of this study was to evaluate autonomic function in patients with polymorphic symptoms and Bartonella henselae IgM seroreactivity. Methods: In this cross-sectional study, 75 patients were compared with 75 age- and sex-matched healthy controls, and all participants underwent cardiovascular autonomic reflex testing, short-term (5 min) and long-term (24 h) heart rate variability analysis, and 24 h ambulatory blood pressure monitoring, while head-up tilt testing was performed in the Bartonella group. Results: Abnormal autonomic reflex tests were significantly more frequent in the Bartonella IgM-seroreactive group, particularly those reflecting parasympathetic function, while heart rate variability analysis demonstrated reduced high-frequency components and lower long-term variability indices, and head-up tilt testing revealed heterogeneous hemodynamic responses including orthostatic hypotension and pronounced blood pressure variability, with ambulatory monitoring additionally showing higher nighttime blood pressure values and reduced nocturnal dipping. Conclusions: These findings indicate a consistent pattern of autonomic imbalance characterized predominantly by parasympathetic impairment and altered blood pressure regulation in patients with Bartonella henselae IgM seroreactivity, although further studies are required to clarify underlying mechanisms and clinical implications.

The paper presents a comprehensive quasi-static digital twin of a utility-scale wind turbine developed in Python. The proposed digital twin framework combines dynamically acquired turbine measurements with static system parameters to reconstruct the steady-state operational behaviour of the wind turbine under real-world conditions. The digital twin integrates historical and real-time operational data to provide dynamic visualization of key performance indicators, enabling continuous insight into turbine behaviour and operational conditions. The model is trained using comprehensive SCADA datasets, including turbine operational data, grid measurements, meteorological observations, and alarm logs, with target variables encompassing the turbine’s active power output and efficiency-related performance metrics. Through systematic data processing, filtering, and aggregation, the digital twin provides a representation of expected turbine behaviour across a wide range of operating conditions. The developed digital twin supports performance benchmarking, operational condition assessment, and early detection of deviations that may indicate aerodynamic inefficiencies, control limitations, or emerging component degradation. Its quasi-static formulation ensures computational efficiency and numerical robustness, making it suitable for real time deployment within wind farm monitoring environments. The presented approach is fully transparent, reproducible, and modular, allowing straightforward extension toward advanced digital twin functionalities, including condition-based maintenance, performance degradation analysis, and integration with forecasting or control-oriented applications. Key words. Digital twin, Wind turbine, Power production, Prediction