Geometric morphometrics has created a significant field in the study of skeletal variation in veterinary osteology by providing a robust framework for investigating shape variation. This technique allows for the analysis of anatomical structures in a variety of biological contexts. This review examines the extant literature, demonstrating how dietary consistency and biomechanical structure significantly shape and often lead to intergenerational morphological changes. The investigation further explores the function of locomotion strategies, including habitat preference and diversity, in the context of the skeletal system. The merits of geometric morphometric analysis are evident in its capacity to facilitate species identification and close relative discrimination in scenarios where conventional methods encounter constraints. The utilisation of geometric morphometric analysis offers distinct advantages in ontogenetic studies, allometric scaling in morphology, and the consideration of developmental constraints. Additionally, it provides a framework for investigating sexual dimorphism and variations in shape across varied species and anatomical regions. From a clinical and welfare perspective, geometric morphometrics provides a powerful framework for orthopaedic surgical planning, detection of pathological changes, phenotyping in animal models, and translational research. Finally, the integration of artificial intelligence (AI)-powered automation and high-resolution imaging is also being reviewed in studies. These developments position geometric morphometrics as an indispensable method for integrating form, function, and health in veterinary research.

Digital technology is now embedded in mathematics classrooms across most school systems, yet the pedagogical question of how such technology should be used to support mathematical learning remains unsettled. Quantitative syntheses report effects ranging from negligible to substantial, large-scale international assessments frequently associate school technology use with weaker mathematical performance, and teacher-level studies show that availability of tools rarely translates into changes in mathematical practice. This critical narrative review examines the state of knowledge on mathematics teaching methodology in digitally mediated settings and develops an integrated pedagogical framework for meaningful technology integration. The review draws on peer-reviewed literature identified through structured searching of open scholarly databases and indexes, supplemented by backward and forward citation searching and by examination of authoritative institutional reports. Evidence was appraised for design adequacy, duration, outcome validity, sample representativeness and consistency with independent findings, and was synthesised thematically rather than study by study. Four critical findings emerge. Aggregate effect estimates are dominated by short, small, researcher-implemented studies, and the largest reported effects cluster in precisely those conditions. Tool-class comparisons show that effects depend on the epistemic function a tool performs rather than on its technical sophistication. Correlational evidence from international assessments cannot be read as evidence of harm, because usage measures conflate remediation, compensation and pedagogy. Teacher enactment, rather than tool provision, is the principal determinant of whether digital mediation alters mathematical activity. The proposed framework organises integration around mathematical purpose, instrumental orchestration, representational congruence, epistemic authority, feedback calibration and equity by design, and distinguishes propositions that are well supported from those that remain conjectural. Generative artificial intelligence intensifies rather than resolves these questions, because it relocates the production of mathematical justification. Priorities for research include longer classroom-embedded trials, process-sensitive outcome measures, and studies that treat teacher orchestration as a manipulated variable rather than as background noise.

This paper explores how generative AI (GAI) may complement, extend or selectively assume information-based functions traditionally associated with human tour guiding in self-guided tourism experiences (SGE). It presents a new framework for GAI-driven SGE, highlighting three central aspects: personalization, real-time support and contextual relevance. To map the relationship between GAI, on-site information-seeking behavior and SGE, we adapted a structured approach based on MacInnis' (2011) framework for explicating (descriptive) conceptual contributions. By utilizing GAI's features, the study shows how GAI may improve tourist independence and convenience. The paper also evaluates the limitations of GAI, particularly its difficulty in replicating the emotional connections, cultural understanding and narrative immersion that human guides provide. Through a comparison with traditional guided tours, the research discusses the consequences of adopting GAI for tourists, service providers and destination management organizations (DMOs). Ethical issues, including data privacy concerns and the potential for cultural inaccuracies, are also explored, along with proposed strategies for responsible implementation. This work lays the groundwork for future studies and real-world applications, offering insights into how GAI may make tourism more adaptable, inclusive and sustainable. While the paper focuses on how GAI may support or selectively assume specific information-based functions of guiding, we recognize that tour guiding is also a form of embodied, relational, and regulated labor that extends beyond the scope of this conceptual framework.

Biliary tract cancers (BTCs) are aggressive malignancies associated with a poor prognosis. Although molecular profiling is recommended to guide therapeutic decision-making, real-practice data on the prevalence and prognostic significance of genomic alterations in European BTC cohorts remain limited. This retrospective cohort study characterized the molecular landscape of BTCs in a Belgian real-practice setting and evaluated its prognostic relevance. Patients with BTC who underwent informative molecular testing as part of routine diagnostics at Antwerp University Hospital between 2016 and 2024 were included. Demographic, clinical, and molecular data were extracted from electronic health records. Survival outcomes were analyzed using Kaplan-Meier methods and Cox proportional hazards regression. Among 224 included patients, genomic alterations were identified in 59.4% of tumors, with clear subtype-specific patterns. IDH1 mutations (17.3%) and FGFR2 fusions (13.9%) were exclusively observed in intrahepatic cholangiocarcinoma, KRAS mutations were most prevalent in extrahepatic cholangiocarcinoma (42.9%), and ERBB2 amplification was enriched in gallbladder cancer (16.7%). Co-occurring alterations were present in 7.8% of cases. KRAS mutation was the most frequent alteration overall (20.4%) and remained significantly associated with worse overall survival in multivariate analysis adjusted for tumor subtype and tumor stage (HR = 1.54, 95% CI: 1.03-2.31, p = 0.04). Although 32.6% of tumors harbored a potentially actionable alteration, only 31.6% of eligible patients received matched targeted therapy. These findings underscore the clinical value of routine molecular profiling in BTC and highlight its importance for identifying therapeutic opportunities in clinical practice.

Introduction People with intellectual disability experience inequalities across the cancer care continuum, including lower screening participation, later-stage diagnosis, and higher cancer related mortality. Whether European cancer prevention and screening policies explicitly address this population has not been systematically mapped. Methods This review aimed to identify and synthesise European national and international policy frameworks, guidelines, and recommendations for cancer prevention and screening that address this population. A systematic search of policy, recommendation and guideline documents across academic databases, grey literature portals, and organisational sources, to August 2025 was under taken. The Population, Concept, Context (PCC) framework guided eligibility. Two reviewers per country screened, extracted, and appraised documents indepen dently using the Authority, Accuracy, Coverage, Objectivity, Date, Significance (AACODS) checklist. Synthesis was narrative, stratified by cancer site and cancer control focus. Results Sixteen documents met the inclusion criteria, originating from five jurisdictions: the United Kingdom, the Netherlands, Belgium, Denmark, and the European Union more broadly. Fifteen of the sixteen addressed cancer screen ing, one also addressed prevention, and two addressed clinical monitoring. Adjustments for people with intellectual disability were concentrated on breast, cervical, and bowel screening and grouped into accessible information, appoint ment adaptations, carer involvement, consent and capacity support, and work force training. Most documents originated from higher expenditure healthcare systems, and no eligible documents were retrieved from the majority of European Union member states. Discussion Policy guidance for cancer prevention and screening for people with intellectual disability is unevenly distributed across Europe and con centrated in a small group of countries. Existing guidance should be extended beyond screening to encompass prevention, treatment, and survivorship, and EU coordination may help address this gap.

Cardiovascular diseases remain the leading cause of morbidity and mortality worldwide, despite significant advances in diagnostics and pharmacotherapy. This persistent burden has shifted attention toward adjunct therapeutic strategies targeting key mechanisms of myocardial and vascular injury, including oxidative stress, mitochondrial dysfunction, endoplasmic reticulum (ER) stress, apoptosis, inflammation, endothelial dysfunction, and metabolic dysregulation. A particular interest of contemporary research is focused on bile acid (BA) signaling through nuclear and membrane receptors, primarily the Farnesoid X receptor (FXR) and Takeda G protein-coupled receptor 5 (TGR5), as central regulators of metabolic, inflammatory, and vascular responses. Ursodeoxycholic acid (UDCA), a hydrophilic BA widely used to treat hepatobiliary disorders, has emerged as a potential modulator of cardiometabolic processes. UDCA exerts direct effects through low-affinity but functionally relevant activation of the TGR5 receptor, as well as indirect effects through alterations in BA pool composition, thereby influencing FXR/TGR5 signaling pathways. Experimental studies suggest that UDCA reduces oxidative stress, stabilizes mitochondrial function, alleviates ER stress, suppresses apoptosis and inflammation, and improves endothelial function and nitric oxide (NO) bioavailability. Despite promising mechanistic evidence, currently available clinical data remain limited and are largely based on small studies and surrogate biomarkers, without confirmation of benefits in terms of major cardiovascular outcomes. This review summarizes current knowledge regarding the role of UDCA in the modulation of BA receptor signaling and its potential relevance for cardiovascular protection.

Background and purpose Anthropometric characteristics such as body height, limb length, and segmental proportions influence sprint performance by affecting stride length, stride frequency, and mechanical efficiency. However, sprint training is often organized according to unified models with limited individualization based on morphology. This study evaluated the effectiveness of anthropometry-specific (differentiated) training programs for sprinters relative to a unified training model of comparable volume and intensity. Material and methods Forty-eight male competitive sprinters (18–25 years, 100–200 m, 4–8 years experience) were assigned to three anthropometric types based on height and leg length index: Type A (tall, long-legged), Type B (medium, balanced), Type C (short, compact). Within each type, athletes were randomized into an experimental subgroup (anthropometry-specific program, EXP) and a control subgroup (unified program, CON) (n=8 per subgroup). All groups trained for 10 weeks (5 sessions/week) with matched volume and intensity. Sprint performance (60 m, 30 m flying, 150 m) and kinematic variables on the 30–50 m segment (stride length, stride frequency, ground contact time) were assessed pre- and post-intervention. Results Baseline sprint performance did not differ significantly between EXP and CON within each type (p>0.5). All groups improved over 10 weeks (p<0.01), but EXP subgroups of Types A and C showed greater gains than their respective CON subgroups. Tall sprinters in A-EXP improved more than A-CON in 60 m, 30 m flying, and 150 m times, while compact sprinters in C-EXP improved more in 60 m time than C-CON. Kinematically, A-EXP showed larger increases in stride length and greater reductions in ground contact time than A-CON, whereas C-EXP showed greater increases in stride frequency and greater reductions in ground contact time than C-CON. For Type B, no significant EXP–CON differences were observed. Conclusions Under matched training volume and intensity, anthropometry-specific programs were more effective than a unified program for tall, long-legged and short, compact sprinters, particularly for maximal speed, speed endurance, and acceleration. For medium-height sprinters, the unified program was not clearly inferior. These findings support the practical value of incorporating anthropometric criteria as one dimension of individualized sprint training design.

PURPOSE To evaluate the feasibility of telemetry-guided optimization of guideline-directed medical therapy (GDMT) and continuous arrhythmic surveillance in ambulatory patients with heart failure with reduced ejection fraction (HFrEF). METHODS TELEMETRIC-HF was a single-center, randomized, open-label pilot study including 30 patients with HFrEF assigned to telemetry-guided management (n=15) or standard outpatient care (n=15). Patients in the telemetry group underwent 8 weeks of continuous ambulatory monitoring using the CPC12 CE MDR Class IIb wearable system, providing continuous electrocardiographic and physiological monitoring with clinician oversight. The primary endpoint was the between-group difference in beta-blocker (BB) target-dose achievement at 8 weeks. Secondary endpoints included optimization of other GDMT classes, ventricular arrhythmia detection, clinical status, quality of life, safety, and healthcare utilization. RESULTS Telemetry-guided management was associated with significantly greater BB target-dose achievement at 8 weeks than standard care (60.0% vs. 39.2% of the guideline-recommended target dose; absolute difference 20.8 percentage points, 95% CI 2.7-39.2; p=0.028). Target-dose achievement for angiotensin receptor-neprilysin inhibitors, mineralocorticoid receptor antagonists, and sodium-glucose cotransporter-2 inhibitors did not differ significantly between groups. Recurrent non-sustained ventricular tachycardia was detected only in the telemetry group, prompting additional clinical evaluation, antiarrhythmic therapy, and primary prevention implantable cardioverter-defibrillator implantation in one patient. Hemodynamic, laboratory, and echocardiographic parameters remained stable throughout follow-up, and telemetry was well tolerated. No heart failure hospitalizations or deaths occurred during the 8-week study period. CONCLUSION In this pilot randomized study, telemetry-guided remote monitoring was feasible and was associated with earlier BB optimization and improved detection of clinically relevant ventricular arrhythmias without compromising safety. These exploratory findings support further evaluation of telemetry-guided outpatient heart failure management in larger, adequately powered multicenter randomized trials.

The aim of this study was to analyse technical and tactical performance indicators in the Croatian First Football League (SuperSport HNL) during the 2025/2026 competitive season. Match analysis has become an essential tool in modern football, allowing coaches, analysts, and researchers to identify performance patterns associated with successful outcomes. This study evaluated offensive and defensive parameters, possession-based indicators, passing efficiency, shots on target, expected goals (xG), pressing intensity, and situational variables related to match outcome. Data were collected from official league statistics and video analysis platforms across all league matches during the observed season. Variables included total passes, successful passes, possession percentage, shots, shots on target, expected goals, duels won, high-intensity pressing actions, recoveries in the final third, and set-piece efficiency. Descriptive statistics and inferential analyses were applied to determine differences between winning, drawing, and losing teams. The results demonstrated that winning teams achieved significantly greater passing accuracy, higher xG values, more successful high pressing sequences, and increased efficiency in transition phases. Teams positioned in the upper part of the league table also showed greater tactical compactness and offensive organization compared to lower-ranked teams. Furthermore, home teams demonstrated statistically significant advantages in ball possession and attacking efficiency. The findings contribute to the growing body of literature regarding notational analysis in elite football and provide practical implications for coaches, analysts, and performance specialists working within Croatian and European football environments.

This study aims to develop a novel Multi Criteria Decision Making (MCDM) methodological model for use as a decision support tool in industrial machine selection problems. To this end, a new integrated MCDM model consisting of Logarithmic normalization and Standard Deviation (LOGSTA), Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), Logarithmic Decomposition of Criteria Importance (LODECI), and Evaluation by Distance from Ideal Solution of Alternatives (EDISA) methods has been designed for a real-world lathe selection problem faced by a manufacturing company in Turkiye. The criterion weights obtained according to the three methods (LOGSTA, LOPCOW, and LODECI) were combined, and the combined criterion weights were transferred to the EDISA method to create an alternative lathe ranking. According to the combined criterion weights, the criterion with the highest importance level was failure frequency (C1), while the criterion with the lowest importance level was active working time (C5). According to the ranking obtained as a result of transferring the combined criterion weights to the EDISA method, the lathe with the highest performance was determined to be Doosan PUMA VT 900 (A2), while the lathe with the lowest performance was determined to be Doosan Puma 300 LM (A1). The comparison analysis shows that the EDISA method produces the same rankings as the ARAS, COPRAS, and RAWEC methods. It is believed that this framework enables manufacturing managers to compare acquisition cost, reliability, operating characteristics, and resale value within a transparent decision process.

Strengthening the connection between physical climate science and adaptation communities is essential for producing actionable, integrated risk information. Here we present a climate impact taxonomy linking 35 climatic impact-drivers to 8 representative key risks, with metadata on climate impact characteristics, relevant subsystems and adaptation–mitigation linkages. This prototype taxonomy enables researchers, practitioners and policymakers to develop adaptation strategies and direct support towards the most urgent, evidence-based priorities across IPCC-aligned dimensions. Adaptation to climate risks requires integrating knowledge across IPCC working groups. This study presents a climate impact taxonomy that connects climatic impact-drivers from Working Group I to representative key risks from Working Group II and provides more direct guidance for risk assessment and adaptation strategies.

Highly pathogenic RNA viruses, such as Ebola, SARS-CoV-2, and influenza, cause severe disease in humans. High mutation rates, which enable RNA viruses to evade immunity and escape antivirals, and their ability to spread from animals to humans and cause pandemics and outbreaks, make RNA viruses significant threats to public health. Diseases caused by Ebola, SARS-CoV-2, and influenza are prevented and treated with only a limited number of approved antiviral drugs, the effectiveness of which is limited by mutations in the viral targets. It is crucial to understand the structural determinants, molecular mechanisms, and host interactions of pathogenic RNA viruses to develop effective antiviral strategies. In this review, we discuss selected RNA viruses, focusing on the structure of their RNA polymerases and interactions with host factors during the different stages of the viral lifecycle, as well as the traditional antivirals targeting these structures and pathways. Furthermore, emerging concepts such as liquid-liquid phase separation and biomolecular condensates, and novel promising antiviral strategies are discussed. Understanding shared and distinct structures, molecular mechanisms, and host interactions across highly pathogenic RNA viruses enables the discovery of new and more effective antiviral strategies, ultimately improving clinical outcomes against evolving RNA viruses.