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.

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 Demand for aesthetic surgery has risen rapidly, and the parallel growth in cross-border medical travel is increasingly burdening European health systems with imported complications. The perspective of board-certified plastic surgeons themselves-as both providers of cross-border care and managers of its complications-has not been systematically captured at a European level. METHODS An anonymous online questionnaire (43 items across three thematic sections) was distributed by the European Society of Plastic, Reconstructive and Aesthetic Surgery (ESPRAS) to its member national societies between December 2025 and February 2026. The instrument addressed (A) the practice of surgeons treating international patients, (B) the management of complications from procedures performed abroad, and (C) safeguards and policy reform. Quantitative data were summarised descriptively; free-text responses were analysed thematically. RESULTS Two hundred and fifty board-certified plastic surgeons from 36 countries responded; 230/250 (92.0%) held national or international board certification. The most common procedures performed for international patients were breast augmentation (n=86), breast reduction/mastopexy (n=82), and abdominoplasty (n=80). Eighty-nine per cent of respondents had managed complications of procedures performed abroad in the preceding five years; abdominoplasty (n=144), breast augmentation (n=106), and liposuction (n=76) predominated, with wound dehiscence/necrosis (n=156) and infection (n=131) the most frequent patterns. Cost was the most often cited primary motivation for patients (49.8%); 79.2% of respondents identified board certification as the single most important verification criterion, and 77.2% identified profit prioritisation over patient safety as the principal facilitator-related risk. Mandatory international qualification standards (35.6%) and stricter facilitator regulation (23.6%) were the most frequently endorsed policy priorities. CONCLUSIONS European plastic surgeons describe a fragmented landscape in which a regulated core coexists with an unregulated commercial periphery. ESPRAS proposes a four-pillar framework-public surgeon registries, facility and facilitator accreditation, mandatory complication insurance, and harmonised European patient- and surgeon-facing guidelines-as the basis of a coordinated European response.

AI-native decision systems — in which generative artificial intelligence generates, executes, and adapts decisions in real time — are shifting the centre of gravity of analytical effort. Whereas the principal challenge used to be the extraction of insight, it is now becoming the validation of AI outputs while action is still being taken upon them. Existing approaches address this problem only partially: explainable artificial intelligence and governance frameworks treat validation as an ex post layer; reinforcement learning reduces it to a single scalar reward; control theory and the broader cybernetic tradition formalise the closed loop but neglect its sociotechnical constraints; while the PRIME–INSPECT framework establishes a governance foundation, yet leaves real-time validation implicit. This paper proposes a validation-centric architecture that links the GAVA decision loop (Generate–Act–Validate– Adapt), introduced here, with the PRIME–INSPECT framework and elevates validation to a central analytical function comprising four subdimensions: statistical, operational, cognitive, and governance-related. The proposed architecture is empirically examined on a dual sample of IT professionals and top-management representatives, using descriptive statistics, multiple regression, mediation, moderation, and structural equation modelling. The results confirm the central role of trust, the negative effect of perceived risk, and the importance of top management support, while robustness checks separated by the IT and TMT subsamples further strengthen the structural model. Taken as a whole, the findings support the view that validation should be treated as a first-order organisational stage in AI-native decision systems.

Residential rooftop photovoltaic (PV) systems are widely deployed in low-voltage networks, where maximizing self-consumption is essential. However, most studies assume balanced three-phase loads, neglecting the inherently single-phase nature of residential appliances. This paper evaluates the impact of phase-aware load modeling on self-consumption in a residential PV system by comparing aggregated and phase-aware representations under normal operation and load-shifting. The load-shifting problem is formulated as a mixed-integer linear programming (MILP) model. Results show that aggregated models systematically overestimate both baseline self-consumption and the benefits of load-shifting. Phase-aware modeling provides more realistic and physically feasible results, although with smaller achievable improvements. These findings highlight the importance of incorporating phase-level modeling for accurate assessment and optimization of residential PV systems.

As 5G and Beyond networks increasingly expose programmable capabilities to vertical industries through standardized APIs such as CAMARA, new challenges emerge regarding efficient and reliable resource orchestration. In this paper we present a vertical-aware orchestration framework based on intelligent edge-deployed network applications that enable real-time coordination between vertical services and the 5G network. We introduce the Quality Awareness EdgeApp, a context-aware solution for dynamic per-UE QoS adaptation using exposed network APIs. The proposed framework is validated in a real-world 5G Standalone deployment at the Port of Antwerp-Bruges (Belgium) for teleoperated vessel operations. Our experimental results demonstrate improved SLA adherence and resource efficiency compared to static slicing and overprovisioning approaches. Our proposed architecture represents a practical step toward adaptive and scalable orchestration for 5G and Beyond vertical services.

Highlights Diabetes abolishes the normal maturational rise of renal SDC1 in rats. SDC2 remains inappropriately elevated in diabetic kidneys at two months. NDST1 is biphasic: raised at two weeks, then profoundly suppressed by two months. Public transcriptomes reproduce the syndecan changes and point to post-transcriptional NDST control. Abstract Background: The aim of this study was to determine the temporal expression patterns of syndecan family members (SDC1, SDC2, SDC4) and heparan sulfate biosynthesis enzymes (NDST1, NDST2) in kidneys of diabetic rats and age-matched controls. Methods: Male Sprague–Dawley rats received intraperitoneal streptozotocin (55 mg/kg; DM1 group) or citrate buffer (control group). Kidney samples were harvested after 2 weeks and 2 months and processed for immunofluorescence. Results: SDC1 showed significant temporal upregulation in controls that was abolished in diabetic animals. SDC2 exhibited high early expression in the control group with significant decline as the kidneys matured but remained elevated in diabetic kidneys at 2 months compared to controls. SDC4 showed no significant difference between groups, though an age-related decrease was observed in controls. NDST1 was significantly upregulated in diabetic rats at 2 weeks, followed by profound suppression at 2 months (p < 0.0001). NDST2 showed modest but significant early elevation in diabetic animals. Transcript-level analysis of two independent public datasets of streptozotocin-induced diabetic rat renal cortex reproduced the principal directional findings—an early increase in SDC1 and a progressive elevation of SDC2—while indicating post-transcriptional regulation of SDC4 and the early NDST response. Conclusions: Diabetes disrupts normal temporal expression of syndecans and heparan sulfate biosynthesis enzymes in rat kidneys. Early compensatory upregulation of NDST1 and NDST2, followed by progressive NDST1 suppression, suggests a deteriorating heparan sulfate biosynthetic capacity, potentially contributing to the progression of diabetic nephropathy.

Vaccination is one of the most effective public health interventions, yet vaccine hesitancy continues to threaten high childhood immunization coverage. Parental attitudes, knowledge, and information sources play a critical role in shaping vaccination decisions, influencing both individual and community protection. A cross-sectional study was conducted between October and December 2024, including 120 parents of children covered by the national vaccination schedule. Data were collected via a self-administered25-item questionnaire distributed through Google Forms, assessing demographics, knowledge, attitudes, and sources of vaccination-related information. Associations between participant characteristics and vaccination attitudes, knowledge, and compliance were analyzed using chi-square tests. Among participants, 95% reported compliance with the mandatory vaccination schedule, and 84.2% expressed a positive attitude toward childhood vaccination. The majority recognized vaccination as primarily benefiting the child (75%) and providing protection against severe disease (72.5%). Healthcare professionals were the main source of vaccination information (71.7%), while media and social networks were less frequently used. Awareness of the anti-vaccination movement was reported by 58.3%, and 43.3% of participants expressed trust in available vaccine information. Compliance was significantly associated with marital status and number of children, while knowledge correlated with educational level. Younger parents and urban residents relied more on media sources, whereas older and rural parents primarily consulted healthcare professionals. The findings indicate that parents in the studied region demonstrate positive attitudes toward childhood vaccination, with high compliance and a strong reliance on healthcare professionals as sources of information. Vaccine hesitancy persists in a minority, often influenced by misinformation and uncertainty. Targeted, prevention-oriented interventions focusing on health communication and support from healthcare professionals are essential to sustain high vaccination coverage and protect children and communities from vaccine-preventable diseases.Keywords: child health, childhood vaccination, health communication, public health, vaccine hesitancy.