Search Results (2,627)

Background: Biliary tract cancers (BTCs), encompassing cholangiocarcinoma and gallbladder carcinoma, are aggressive malignancies with poor prognosis and increasing incidence in selected regions worldwide. Advances in imaging, biomarker profiling, immunotherapy, and targeted therapies have improved treatment options but have also increased the economic pressure on health systems. Understanding the economic evidence on BTC is therefore important for resource allocation and health technology assessment. Methods: We systematically searched PubMed/MEDLINE, Embase, Scopus, and Web of Science for peer-reviewed economic studies of BTC published from January 2010 to March 2025. Eligible studies included cost-effectiveness, cost–utility, cost–benefit, cost-of-illness, and resource-use analyses. The review followed PRISMA reporting principles. Reporting completeness was assessed using CHEERS 2022, and methodological credibility was appraised using the Drummond framework. Results: Twenty studies were included: 13 cost-effectiveness or cost–utility analyses and seven cost-of-illness or resource-use studies. Conventional chemotherapy strategies, including gemcitabine plus cisplatin in some settings and other cytotoxic combinations in selected jurisdictions, generally produced more favorable economic results than newer systemic therapies, although findings varied by country, threshold, comparator, and price assumptions. First-line immunotherapy combinations and biomarker-directed targeted therapies frequently produced ICERs above jurisdiction-specific willingness-to-pay thresholds at current prices, often requiring substantial price reductions to approach cost-effectiveness. Real-world studies showed high resource use and costs, particularly with hospitalizations and later treatment lines. Evidence on screening and prevention was limited, with one study suggesting that ultrasound surveillance may be cost-effective in a liver fluke-endemic region of Thailand. Discussion: The available economic evidence suggests that affordability and jurisdiction-specific value assessment are central to BTC policy decisions. Current prices for several immunotherapy and targeted agents limit cost-effectiveness in published models, while evidence on prevention, early detection, and care-pathway interventions remains sparse and context-specific. Full article

Non-attributed graph sequence offers a powerful formalism for modeling the structural dynamics of complex systems—such as social networks, urban infrastructures, and document transmission pathways—where vertex interactions evolve over time without explicit attribute information. Mining association rules from such sequences to uncover recurring topological patterns have attracted growing interest. Yet two fundamental challenges remain: (1) how to effectively encode edge-level temporal dynamics in non-attributed settings, and (2) how to perform efficient and semantically meaningful temporal association rule mining under structural uncertainty. To address these within a systems-oriented framework, we propose two novel algorithms: the weighted temporal association rule mining algorithm and the fuzzy weighted temporal association rule mining algorithm. The first algorithm introduces time-dependent numerical weights to quantify the strength and persistence of vertex connectivity, integrating them into support and confidence measures to capture both the intensity and evolution of interactions. The second algorithm extends this by incorporating fuzzy set theory, modeling ambiguous or context-sensitive relationships (e.g., indistinct links or weakly correlated vertices) and generating fuzzy-weighted rules that enhance interpretability for real-world system analysis. Evaluated through five comprehensive experiments across diverse datasets and scales using standard metrics (support, confidence, rule count, running time), our methods produce more selective rule sets and achieve lower computational times compared to the classical Apriori algorithm. The proposed approaches thus establish a robust, data-driven foundation for analyzing temporal evolution and structural uncertainty in dynamic complex systems—providing a generalizable methodology applicable beyond domain-specific constraints. Full article

Intelligent Transportation Systems (ITS) play a central role in the development of more efficient, adaptive, and resilient road networks. Traffic control strategies have progressively evolved from traditional approaches toward more intelligent and adaptive frameworks. This paper presents a taxonomy-based perspective on intelligent traffic control strategies for road networks, organizing existing approaches according to three complementary dimensions: control scope, decision-making mechanism, and control architecture. Based on this framework, the paper discusses representative methodologies, including rule-based control, model-based methods, simulation-based optimization, data-driven and artificial intelligence-based methods, and emerging cooperative strategies enabled by connected and automated vehicles (CAVs). The analysis also examines key application domains, such as traffic signal control, ramp metering, CAV-based traffic management, and simulation platforms, highlighting their operational principles, advantages, limitations, and implementation challenges. Particular attention is given to the transition from local and reactive control toward coordinated, predictive, and learning-based traffic management systems. The paper identifies major challenges related to scalability, robustness, interpretability, safety, real-world deployment, and the gap between simulation performance and practical implementation. The proposed taxonomy also supports practical comparison and preliminary selection of context-specific strategies. Future directions point toward integrated and hybrid frameworks combining data-driven adaptability, vehicle–infrastructure cooperation, and digital twin technologies. Full article

Background/Objectives: Advanced hormone receptor-positive (HR+), epidermal growth factor 2-negative (HER2−) breast carcinoma (BC) patients receive frontline therapy with cyclin-dependent tyrosine kinase 4/6 inhibitors + endocrine therapy (ET). At progression, the best management includes mutational analysis for ESR-1, allowing second-line therapy with elacestrant. The aim of this study was to evaluate the efficacy and safety of elacestrant in an Italian real-world setting. Methods: A multicenter, observational study with a mixed retrospective and prospective design was conducted in 13 medical oncology units across Italy. The study population included adult patients with HR+/HER2− locally advanced or metastatic breast cancer with an activating ESR1 mutation documented by liquid biopsy and progressing after at least one line of endocrine therapy containing a CDK4/6 inhibitor. Mutational analysis of plasma was performed using next-generation sequencing with a multigene panel that included ESR1, PIK3CA, AKT, and PTEN. The sample size was calculated according to the two-stage Simon design. Toxicity was classified according to CTCAE version 5.0 criteria. Survival analyses were conducted using the Kaplan–Meier method. Results: At the time of analysis, 39 evaluable patients were enrolled, all female and Caucasian, with a median age of 67 years (range 41–89). The efficacy analysis documented an overall ORR of 28% and a disease control rate of 56%. The median duration of response was 6+ months (95% CL: 3.5–10.6 m). Median overall survival was not reached with a median follow-up of 10 months. The toxicity profile was overall favorable: grade ≥2 asthenia was the most frequent adverse event (23%), followed by gastrointestinal toxicity, which was generally mild. No treatment-related toxicity was reported in 64% of patients. Dose reductions were necessary in 15% of cases, while permanent treatment discontinuation due to toxicity occurred in only 4%. Conclusions: The results of this Italian multicenter observational study confirm the efficacy and tolerability of elacestrant in HR+/HER2− metastatic breast cancer with ESR1 mutation, in a real-world context consistent with the data from the pivotal EMERALD study and with real-world data present in the literature. Full article

Rising cancer incidence and survival rates have led to an unprecedented demand for psychosocial care. Yet, limited financial and practical resources present a barrier to the provision of evidence-based care. Clinical practice guidelines (CPGs) are well-positioned to enhance the quality and efficiency of psychosocial oncology care; however, little is known about their use and perceptions in the field. The present study explored the use and perceptions of CPGs among 172 Canadian psychosocial oncology clinicians via a cross-sectional, online survey. Findings revealed substantial variation in awareness, with over 20% of participants reporting no familiarity with CPGs, and low to moderate use of CPGs (M = 2.97, SD = 2.96) among users. Key barriers included a lack of formal training, limited applicability to local contexts, and systemic constraints such as high workloads. Conversely, participants highly endorsed facilitators, including accessible training programs, relevant tools/interventions, and greater institutional and community engagement. Clinician perspectives are paramount to the dissemination and implementation of psychosocial oncology CPGs. Our findings suggest that successful implementation requires broader accessibility, widespread adaptation, and greater community engagement. By addressing these systemic constraints, CPGs may be better positioned to bridge the gap between evidence and real-world service provision. Full article

Hypertension is among the most important modifiable risk factors associated with heart failure with preserved ejection fraction (HFpEF) development and progression, yet guideline-directed blood pressure (BP) targets (<130/80 mmHg) and sodium–glucose co-transporter 2 inhibitor (SGLT2i) therapies lack dedicated randomized controlled trials (RCTs) in this specific group of patients. This narrative review synthesizes 2024 ESC/ESH and 2025 JSH meta-analyses, discussing the proposed pathophysiological framework linking hypertension-associated remodeling with HFpEF. Post hoc analyses from landmark trials (EMPEROR-Preserved, DELIVER) demonstrate consistent heart failure (HF) event reductions with SGLT2i (pooled HR 0.79, 95% CI 0.67–0.93), complemented by modest systolic BP lowering (−2.3 mmHg) and biomarker insights. Soluble ST2 and N-terminal pro-B-type natriuretic peptide (NT-proBNP) may contribute to risk stratification in HFpEF populations when interpreted in conjuction with imaging findings and clinical context; however, neither biomarker is specific for hypertension-mediated remodeling. Critical evidence gaps persist: heterogeneous BP thresholds across international guidelines, limited device therapy data (renal denervation showing −8.5 mmHg sustained reduction), and real-world implementation barriers among elderly/comorbid Europeans (adherence < 50%, polypharmacy risks). Hellenic HF Registry data highlight frailty prevalence (68% in patients > 75 years) complicating aggressive BP management. The review addresses phenotype-specific challenges through precision medicine approaches incorporating phenomapping and multi-biomarker panels (NRI 0.28 improvement). We advocate for dedicated HFpEF RCTs evaluating intensive vs. standard BP targets, SGLT2i sequencing with antihypertensives, and European real-world registries to bridge the translational gap. These strategies aim to transform guideline recommendations into optimized, patient-centered care for the rapidly expanding hypertensive HFpEF population. Full article

Background: Patients with mild traumatic brain injury (mTBI) have a small but clinically relevant risk of intracranial injury (ICI), requiring timely detection. Computed tomography (CT) remains the diagnostic gold standard but is costly and exposes patients to ionising radiation. Combining blood-based biomarkers, glial fibrillary acidic protein (GFAP) and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), with clinical decision rules may allow safe exclusion of ICI without CT, reducing unnecessary imaging, radiation exposure, and resource use. Methods: A systematic review of clinical and economic studies in patients with mTBI was registered in PROSPERO (CRD420251051158). Searches were conducted in January 2025 and updated in May 2025 in MEDLINE, Embase, and the Cochrane Library. The aim was to assess the diagnostic accuracy and economic value of the combination of GFAP and UCH-L1 compared with CT scanning to rule out ICI in both adults and children with mTBI. Where available, studies directly comparing GFAP and UCH-L1 with S100β were also analysed descriptively. The quality of the clinical evidence was assessed with QUADAS-2 and GRADE. Meta-analyses used a bivariate random-effects model, with heterogeneity and sensitivity analyses explored. Results: Overall, 21 studies were considered in our review. Moderate- to high-quality evidence indicates that GFAP and UCH-L1, when used together with clinical assessment, have very high sensitivity and can reliably rule out ICI in adults with mTBI presenting within 12 h to the emergency department. Evidence for paediatric populations shows promise but remains very limited. Specificity is low, particularly in older adults, which limits the ability to reduce CT use in this high-risk group. Research on age-adjusted cut-offs is ongoing and may help to reduce the proportion of false positive tests without compromising sensitivity. Few studies directly compared GFAP and UCH-L1 with S100β, with slightly higher to equivalent sensitivity for GFAP and UCH-L1. Economic evaluations suggest possible cost savings and reduced CT utilisation, but these analyses rely on assumptions unsupported by robust data and are highly context-dependent. There is a lack of clarity in the included studies regarding whether existing clinical head rules were used to define the study populations (i.e., to determine which patients would be recommended for CT scanning) and, if so, which specific rules were applied. Conclusions: Evidence shows that GFAP and UCH-L1 can safely exclude ICI in adults with mTBI in whom a CT scan would otherwise be considered based on clinical assessment or decision rules. Nevertheless, real-world evidence and cost-effectiveness data are scarce. Further prospective studies, including paediatric and elderly populations, and integration with clinical decision rules will be informative to ensure optimal use in clinical practice. Full article

Short-term water demand forecasting is a key issue for the management of smart water networks, particularly in the context of remote control and active regulation. This study analyses a real-world dataset of water demand coefficients, collected at 15 min intervals, from a municipality in Southern Italy serving approximately 73,000 inhabitants. The proposed model, based on Gaussian Process Regression (GPR) with a Rational Quadratic kernel (RQ), is compared with a statistical benchmark constructed using average patterns for each time slot by the application of the Gauss Distribution. The results show a reduction in RMSE and MAE and a better ability to track the daily dynamics of demand using the GPR approach. Full article

The implementation of medication adherence interventions is suboptimal. To guide implementation, this study aimed to tailor an existing implementation determinant framework to support the assessment of the implementability of such interventions in a specific context prior to implementation, and to investigate whether experts can assess in advance which determinants are important for implementing medication adherence interventions. In a Delphi study, experts rated determinants based on constructs of the Consolidated Framework for Implementation Research (CFIR) in terms of their importance for implementing medication adherence interventions. Determinants were then prospectively evaluated in four Dutch living labs implementing medication adherence interventions. The results were compared to assess agreement between expert opinion and real-world practice. Of 40 evaluated CFIR determinants, 16 were important in the majority of the living labs. These determinants concerned the inner setting, characteristics and roles of involved individuals, and implementation process domains of the CFIR. After comparing the prospective evaluation with Delphi results, expert opinions matched living lab observations for 18 out of 40 determinants (45%) regarding (un)importance. The CFIR was tailored to primary care medication adherence interventions based on practice observations, offering a potentially helpful framework to assess implementability of these interventions in specific contexts in advance. Determinant frameworks could benefit from incorporating real-world practice data. Full article

This study aims to improve wagon unloading processes in a real industrial context characterized by operational variability, process constraints, and strict performance requirements. Traditional decision-making approaches in such contexts often rely on single performance indicators, which may lead to suboptimal and less sustainable decisions. In line with Industry 5.0 principles, which emphasize human-centricity, resilience, and sustainability, this paper proposes a multi-criteria decision framework to support more balanced and adaptive operational decisions. A real-world case study based on anonymized industrial data is used to evaluate different arrival-track operational configurations. The proposed model considers several indicators, including unloading time, throughput, tonnage, process variability, operational losses, and a proxy of operator exposure. To strengthen the human-centric dimension, an Operational Handling Exposure Proxy (OHEP) was introduced to capture manoeuvre-related operator exposure during wagon handling and batch repositioning. A weighted scoring system was then used to identify the most balanced configuration by considering trade-offs between performance, stability, losses and operator exposure. The results show that the arrival-track operational configuration influences loss structure, process stability and overall decision ranking more than direct throughput alone. Track 2 provides the best overall trade-off under the baseline MCDM weighting scheme, while Track 3 may become preferable when wagon-loss minimization is prioritized. The findings highlight the importance of integrating variability and human-centered indicators into industrial decision-making processes. In future work, the proposed framework could be extended using data-driven methods and machine learning to support predictive and adaptive optimization in Industry 5.0 environments. This study contributes to the literature by integrating real-world industrial analysis, multi-criteria decision-making, and sustainability-oriented optimization into a single decision support framework. Full article

Background/Objectives: Digital, remote, and ecological tools may complement clinic-based assessment in multiple sclerosis (MS), but the distribution of evidence across fatigue/fatigability, mobility, and real-world functional activity remains unclear. This scoping review mapped tools, metrics, constructs, contexts of use, and reported clinical utility in adults with MS, with attention given to whether the evidence was balanced across domains. Methods: Following Joanna Briggs Institute guidance and PRISMA-ScR/PRISMA-S reporting standards, five databases were searched on 14 March 2026. After deduplication, title/abstract screening, full-text assessment, and manual extraction and verification, the findings were synthesized descriptively without formal critical appraisal. Results: Of 3100 records identified, 1433 unique records were screened and 125 sources were included. Gait was the most frequently assessed domain (105/125), followed by fatigue/fatigability (33/125), physical activity (29/125), and sleep (2/125). The most frequent technologies were wearable devices (60/125), accelerometry (54/125), remote/home-based/telemonitoring modalities (52/125), and inertial measurement units (42/125). Conclusions: The evidence is predominantly gait- and mobility-focused, while fatigue/fatigability and broader real-world functional activity are less consistently represented. Reported clinical utility was usually framed around functional assessment, longitudinal/remote monitoring, rehabilitation planning, patient stratification, and decision support, but these characteristics were extracted as reported and were not independently appraised. Full article

Developing critical thinking is a central aim of contemporary higher education, yet conventional instructional approaches often underuse authentic, real-world materials that stimulate higher-order reasoning and reflective judgment. The study examines the effectiveness of case-based socio-legal pedagogy in fostering critical thinking within contexts of legal pluralism and social complexity. A quasi-experimental mixed-methods pre–post design was conducted with 62 undergraduate students enrolled in a course on Islamic law and society. Over a four-week intervention, students engaged with six socio-legal cases drawn from Muslim women’s legal experiences in Israel, focusing on divorce, maintenance (nafaka), and child custody. Quantitative data were collected using a validated Critical Thinking Rubric assessing argumentation, evaluation of multiple perspectives, and legal reasoning. Results showed significant improvement in overall critical thinking, with gains across all measured dimensions. Qualitative analysis of written assignments and student reflections revealed greater recognition of legal ambiguity, more structured and evidence-based argumentation, and deeper engagement with competing normative and social frameworks. Overall, the findings highlight the pedagogical value of integrating socio-legal complexity into case-based learning as an adaptable model for strengthening critical thinking across disciplines involving interpretive, contested, and context-dependent knowledge in higher education and other fields requiring careful judgment under conditions of uncertainty and change. Full article

The rapid emergence of generative AI tools is transforming software development. Consequently, software engineering education must adapt to ensure that students not only learn traditional development methods but also understand how to use these new technologies effectively and responsibly. In particular, project-based courses provide an effective setting in which to explore and evaluate the integration of AI assistance into real-world development practices. This paper presents our approach and a user study conducted in the context of a university programming project in which students collaboratively developed computer games. The study investigates how participants used generative AI tools across different phases of the software development process, identifies the tasks for which these tools were perceived as most useful, and analyzes the challenges students encountered. Building on these insights, we further examine a repository-aware, locally deployed large language model (LLM) assistant designed to provide project-contextualized support. The system employs retrieval-augmented generation (RAG) to ground its responses in relevant documentation and source code, thereby enabling a qualitative analysis of model behavior, parameter sensitivity, and common failure modes. These findings deepen our understanding of context-aware AI support in educational software projects and inform the future integration of AI-based assistance into software engineering curricula. Full article

Mindful pedagogy integrates a mindful approach in the classroom to support learning, creativity, and wellbeing using formal meditative practice or informal subject-related mindful practice or both. Since 2019, Mindful Kitchen Health and Wellbeing for Chefs, a globally unique module, has been delivered within year 1 of an undergraduate culinary arts programme. It uses a mindful pedagogical approach in a teaching kitchen setting promoting student self-care, mindfulness with food and positive kitchen culture. This qualitative single-case study explores its impact on the wellbeing of chefs in a real-world context and the process that creates that impact. The case study database includes interviews with graduates (n = 11), students (n = 7), module artefacts, co-creation workshops, and researcher reflection on class observations. Four themes emerged: stepping into wellbeing using the breath builds self-awareness, a mindful classroom builds creative confidence, calm minds empower the self for the workplace and informal mindful pedagogy creates “spacious applied learning” in Higher Education (HE). These unique insights can inform wellbeing-focused pedagogical practice in HE settings. Students’ experiences are easily transferable into other disciplines; however, further research should investigate nuances in transferability. Recommendations on integrating this approach into educators’ practice to strengthen wellbeing-focused teaching are presented. Full article

Background/Objectives: Curcumin has been proposed as a nutritional strategy to support exercise recovery through antioxidant and anti-inflammatory actions. However, trials differ in sport context, training status, supplementation timing, dose, formulation, and methodological control. This systematic review evaluated its effects on recovery outcomes in active individuals and athletes, with particular attention to the applicability of the evidence to real-world sport settings. Methods: PubMed, Scopus, Web of Science, SPORTDiscus, and Cochrane Library/CENTRAL were searched from 2012 to June 2026. Randomized double-blind placebo-controlled trials were eligible when they evaluated oral curcumin, curcuminoids, Curcuma-derived preparations with a specified curcumin dose, or curcumin combined only with bioavailability enhancers. Studies using artificial muscle-damage protocols, clinical populations, non-randomized designs, or combined bioactive interventions were excluded. Methodological quality was assessed using the Physiotherapy Evidence Database (PEDro) scale, supplemented by a Cochrane Risk of Bias 2 (RoB 2) assessment and a Grading of Recommendations Assessment, Development and Evaluation (GRADE) certainty-of-evidence evaluation. Owing to heterogeneity, findings were synthesized narratively by outcome domain, supplementation timing, formulation type, exercise context, and training status. Results: Fifteen trials were included. Favorable effects were reported in 6/7 studies assessing oxidative stress, 4/6 assessing muscle damage, 3/8 assessing inflammation, 3/7 assessing subjective recovery, soreness, or fatigue, and 4/8 assessing physical or athletic performance. However, effects varied substantially according to population, exercise context, biomarker selection, timing of assessment, and formulation type. The certainty of evidence was low for oxidative stress and very low for muscle damage, inflammation, subjective recovery/soreness/fatigue, and performance. Conclusions: Curcumin supplementation may support selected aspects of exercise recovery, particularly oxidative stress responses. However, these findings should be interpreted cautiously because the evidence derives mostly from small trials with heterogeneous populations, exercise protocols, supplementation regimens, formulations, biomarkers, and assessment time points. Evidence for muscle damage, inflammation, subjective recovery, fatigue, and performance remains inconsistent, and further well-controlled trials in trained and high-performance athletes are needed before practical recommendations can be established. Full article