Search Results (12,832)

Cardiac inflammation and hypertrophy develop as a pathologic response to an array of insults, such as myocardial infarctions, chronic systemic hypertension, and valvular defects. Due to the high prevalence of such conditions, there is an increasing need to prevent and halt cardiac hypertrophy. Because cardiac damage and subsequent remodeling can lead to arrhythmias, heart failure, and even sudden cardiac death, inhibition of cardiac hypertrophy is key to reducing cardiovascular-related mortality. The immune system is the driving force behind inflammatory reactions. All three pathways of complement system activation—classical, lectin, and alternative—are implicated in developing cardiac damage, inflammation, and hypertrophy due to infectious and non-infectious causes, autoimmune diseases, genetic polymorphisms, and forms of complement dysregulation. Of interest in this review is the role of the complement system, a collection of soluble and membrane-bound proteins that mediate inflammatory processes through interactions with signaling molecules and immune cells. This review comprehensively discusses the roles of these complement pathways in contagious, chronic inflammatory, genetic, and metabolic diseases. An overview of the completed and terminated clinical trials aimed at preventing cardiovascular mortality by targeting various aspects of the complement system and inflammatory reaction is included. Most current treatments for cardiac inflammation and remodeling primarily target the renin–angiotensin–aldosterone system (RAAS), which prevents further remodeling by reducing myocardial workload. However, moving forward, there may be a place for emerging anti-complement therapeutics, which impair the inflammatory response that generates hypertrophy itself. Full article

The shadow economy weakens fiscal sustainability, hampers the financing of public goods, and impedes the achievement of sustainable development goals. The informal sector remains a persistent challenge for policymakers, as it distorts competition, reduces transparency, and undermines the effectiveness of economic and fiscal policies. The aim of this article is to identify the key factors determining the size of the shadow economy in European Union countries and to provide policy-relevant insights. The analysis covers data on the share of the informal economy in GDP and macroeconomic variables such as GDP per capita, consumer price index, average wages, household consumption, government expenditure, and unemployment, as well as indicators of digital development in society and the economy (DESI, IDT), the share of cashless transactions in GDP, and information on the implementation of digital tax administration tools and restrictions on cash payments. Five hypotheses (H1–H5) are formulated concerning the effects of income growth, labour market conditions, digitalisation, cashless payments, and tax administration tools on the shadow economy. The research question addresses which factors—macroeconomic conditions, economic and social digitalisation, payment structures, and fiscal innovations in tax administration—play the most significant role in determining the size of the shadow economy in EU countries and whether these mechanisms have broader implications for fiscal sustainability and sustainable development. The empirical strategy is based on multilevel models with countries as clusters, complemented by correlation and comparative analyses. The results indicate that the most significant factor in limiting the size of the shadow economy is the level of GDP per capita and its growth, whereas the impact of card payments appears to be superficial, reflecting overall increases in wealth. Higher wages, household consumption, and digital development as measured by the DESI also play an important role. The implementation of digital solutions in tax administration, such as SAF-T or e-PIT/pre-filled forms, along with restrictions on cash transactions, can serve as complementary measures. The findings suggest that sustainable strategies to reduce the shadow economy should combine long-term economic growth with digitalisation and improved tax administration, which may additionally foster the harmonisation of economic systems and support sustainable development. Full article

Introduction: Renal cell carcinoma (RCC) develops metastatic disease in 30–50% of patients during their disease course, with approximately one quarter presenting with metastases at diagnosis. While the lungs, liver, bones, brain, and adrenal glands are the most frequent metastatic sites, duodenal involvement is exceptionally rare. This uncommon presentation poses diagnostic and therapeutic challenges, particularly regarding the role of surgical resection in the metastatic setting. Objective: We aim to evaluate the clinical presentation, management strategies, and outcomes of patients with duodenal metastasis from RCC, with particular emphasis on the potential role of surgery, through a systematic review of the literature. Methods: A comprehensive electronic search of Medline, Embase, and Scopus was conducted according to PRISMA guidelines. The following MeSH terms were applied: Kidney Neoplasms [MeSH] AND Duodenal Neoplasms/metastasis [MeSH]. Eligible studies included original reports or case series describing RCC with duodenal metastasis. Demographic, clinical, surgical, and survival data were extracted and synthesized. Results: Of 89 records identified, 83 underwent full-text review and 51 met inclusion criteria, representing 55 patients. The median age at diagnosis was 64 years, and 80% of primary tumors arose from the right kidney. Nearly all patients (98%) were symptomatic, most commonly with upper gastrointestinal bleeding, anemia, or obstructive features. Pancreaticoduodenectomy was the predominant surgical approach, performed with curative intent in selected cases. Patients undergoing surgery achieved a 5-year overall survival of 70%, compared with 0% among non-operated patients. Conclusions: Duodenal metastasis from RCC remains an uncommon entity, limiting the strength of available evidence. Nevertheless, our findings suggest that surgical management—when feasible and decided within a multidisciplinary framework—can provide meaningful survival benefit and should be considered as a complement to contemporary systemic therapies for metastatic RCC Full article

Background: Cardiovascular diseases (CVDs) remain the primary cause of global mortality, with arterial hypertension, ischemic heart disease (IHD), and cerebrovascular accident (CVA) forming a progressive continuum from early risk factors to severe outcomes. While numerous studies focus on isolated biomarkers, few integrate multidimensional visualization with artificial intelligence to reveal hidden, clinically relevant patterns. Methods: We conducted a comprehensive analysis of 106 patients using an integrated framework that combined clinical, biochemical, and lifestyle data. Parameters included renal function (glomerular filtration rate, cystatin C), inflammatory markers, lipid profile, enzymatic activity, and behavioral factors. After normalization and imputation, we applied correlation analysis, parallel coordinates visualization, t-distributed stochastic neighbor embedding (t-SNE) with k-means clustering, principal component analysis (PCA), and Random Forest modeling with SHAP (SHapley Additive exPlanations) interpretation. Bootstrap resampling was used to estimate 95% confidence intervals for mean absolute SHAP values, assessing feature stability. Results: Consistent patterns across outcomes revealed impaired renal function, reduced physical activity, and high hypertension prevalence in IHD and CVA. t-SNE clustering achieved complete separation of a high-risk group (100% CVD-positive) from a predominantly low-risk group (7.8% CVD rate), demonstrating unsupervised validation of biomarker discriminative power. PCA confirmed multidimensional structure, while Random Forest identified renal function, hypertension status, and physical activity as dominant predictors, achieving robust performance (Accuracy 0.818; AUC-ROC 0.854). SHAP analysis identified arterial hypertension, BMI, and physical inactivity as dominant predictors, complemented by renal biomarkers (GFR, cystatin) and NT-proBNP. Conclusions: This study pioneers the integration of multidimensional visualization and AI-driven analysis for CVD risk profiling, enabling interpretable, data-driven identification of high- and low-risk clusters. Despite the limited single-center cohort (n = 106) and cross-sectional design, the findings highlight the potential of interpretable models for precision prevention and transparent decision support in cardiovascular aging research. Full article

Parasites of the Leishmania genus are globally distributed and cause various clinical presentations in animals and humans, collectively known as leishmaniasis. The genomes of Leishmania and other trypanosomatids exhibit remarkable plasticity, shaped by several distinctive genetic features. Although these features can hinder the application of next-generation DNA sequencing (NGS) technologies, NGS data have been successfully used to characterize the whole-genome diversity of circulating Leishmania strains. The results complement and are broadly aligned with previous findings obtained with more traditional methods, offering greater resolution when working with geographically closer strains. In this review, we summarize advances over the past two decades in characterizing the genome diversity of Leishmania parasites using NGS strategies. We also discuss the application of these strategies to elucidate other aspects relevant to the epidemiology of these parasites, including their population structure and mode of reproduction. The vast majority of the studies to date have focused on species within the L. donovani/infantum complex or the L. (Viannia) subgenus, highlighting the need to incorporate other relevant underrepresented species and regions from both the Old and New World. Full article

Background/Objectives: Nasal biopharmaceutics is the scientific understanding of product and patient factors that determine the rate and extent of drug exposure following nasal administration. The authors considered whether current biopharmaceutics tools are fit for the current and future needs of nasal product development and regulation. Methods: The limitations of current methods were critically assessed, unmet needs were highlighted, and key questions were posed to guide future directions in biopharmaceutics research. Results: The emergence of physiologically based biopharmaceutics models for nasal delivery has the potential to drive the scientific understanding of nasal delivery. Simulations can guide formulation and device development, inform dose selection and generate mechanistic insights. Developments in modeling need to be complemented by advances in experimental systems, including the use of realistic or idealized nasal casts to estimate the regional deposition of nasal sprays and refined in vitro cell culture models to study nasal drug absorption and the influence of mucus. Similarly, improvements are needed to address the practicalities of using animals in non-clinical studies of nasal drug delivery, and greater clinical use of gamma scintigraphy/magnetic resonance imaging is recommended to measure the delivery and nasal retention of different formulations in humans. Conclusions: Nasal drug delivery is a rapidly growing field and requires advances in nasal biopharmaceutics to support product innovation. Key needs are (i) validated clinically relevant critical product attributes for product performance and (ii) established links between how patients administer the product and where in the nose it deposits and dissolves in order to act or be absorbed, leading to its desired clinical effect. Full article

Nowadays, the potential of hydrokinetic turbines as a sustainable alternative to complement traditional hydropower is widely recognized. This study presents a comprehensive numerical analysis of twin straight-bladed Darrieus hydrokinetic turbines, characterizing their hydrodynamic interactions and performance characteristics. The influence of turbine configuration spacing and flow parameters on efficiency and wake dynamics are investigated. The employed 3D computational approach combines the overset mesh technique, used to capture the unsteady flow around the turbines, with the URANS k-ω Shear Stress Transport (SST) turbulence model. Results show that turbine spacing improves power coefficients and overall efficiency, albeit at the cost of slower wake recovery. A noticeable performance increase is observed when the turbines are spaced between 1.5 and 2 diameters apart, which is predicted to reach up to 40% regarding the single turbine. Furthermore, the effect of flow interaction between the turbines is examined by analyzing the influence of turbine spacing on flow structures as well as pressure and skin friction coefficients on the blades. The performed analysis reveals that vortex detachment is delayed in the twin-turbine configuration compared to the isolated case, which partially explains the observed performance enhancement. The insights gained from this work are expected to contribute to the advancement of renewable hydrokinetic energy technologies. Full article

Background and Objectives: Periodontitis is a common chronic inflammatory disease and a leading cause of tooth loss worldwide. Traditional diagnostic methods, such as probing and radiographic assessment, are retrospective and fail to detect ongoing disease activity. In recent years, salivary biomarkers and oral microbiome profiling have emerged as promising tools for earlier detection and precision-based management. The aim of this review is to synthesize current evidence on salivary and microbiome-derived biomarkers in periodontitis and to evaluate their translational potential in diagnostics and therapy. Materials and Methods: A narrative review was performed using PubMed, Scopus, and Web of Science to identify studies published between 2020 and 2025. Search terms included periodontitis, salivary biomarkers, oral microbiome, dysbiosis, and precision therapy. Priority was given to systematic reviews, meta-analyses, and translational studies that addressed diagnostic or therapeutic applications. Eligible publications included English-language original studies and reviews reporting on the diagnostic or therapeutic relevance of salivary or microbiome biomarkers in periodontitis. Results: Salivary biomarkers such as cytokines, matrix metalloproteinases (MMPs), oxidative stress markers, microRNAs, and extracellular vesicles (EVs) show consistent associations with disease activity and treatment outcomes. Oral microbiome studies reveal that both classical pathogens and community-level dysbiosis contribute to disease risk. Translational advances include chairside immunoassays, biosensors, lab-on-a-chip devices, and artificial intelligence (AI)-driven analyses. Biomarker-guided therapies—such as microbiome modulation, natural bioactive compounds, host-response modulation, and smart biomaterials—are being evaluated with increasing frequency in translational studies. Conclusions: By integrating salivary and microbiome biomarkers with novel diagnostic technologies and emerging therapies, this review complements existing systematic evidence and offers a translational roadmap toward precision periodontology. Full article

Collaborative Online International Learning (COIL) has become an innovative pedagogical strategy that promotes the internationalization of curricula and the development of transversal competencies. In architecture, its implementation is particularly relevant because there is a growing need to train professionals capable of leading and collaborating in global and interdisciplinary contexts. However, evidence of COIL’s impact during the early stages of higher education in Latin America remains limited. This study analyzed the experience of 39 architecture students from the Universidad Nacional de San Agustín de Arequipa (Peru), who collaborated with peers from Mexico in a five-week COIL project focused on design methodologies for vulnerable populations. Using a mixed-methods approach, the study assessed students’ competencies in leadership, self-regulation in virtual learning, and emotional intelligence and teamwork through pre- and post-experience questionnaires complemented with open-ended questions. Findings indicate that although students’ self-perceptions of their competencies remained at medium-to-high levels overall, changes occurred differently among groups: students with initially low self-assessment scores showed improvements, whereas those with initially high scores tended to moderate their self-assessment. Qualitative analysis highlighted barriers such as limited communication, time zone differences, and unequal participation. Overall, the results suggest that the COIL experience not only supported the development of competencies but also fostered critical reflection and a more realistic self-assessment of students’ competencies in virtual and intercultural contexts. Full article

Background: The digital transition is reshaping healthcare systems through the adoption of telemedicine and electronic health records (EHRs). While these innovations enhance efficiency and access, their implementation unfolds within overstretched organizational settings characterized by workforce shortages, bureaucratic demands, and heightened psychosocial risks. Burnout, impostor syndrome, and the quality of organizational support have thus become pivotal constructs in understanding healthcare professionals’ digital preparedness. Methods: A cross-sectional online survey was conducted among 111 professionals employed at two San Donato Group facilities in Bologna, Italy. The battery included socio-demographic and occupational data, perceptions of digitalization, and validated instruments: the Maslach Burnout Inventory (MBI), the Clance Impostor Phenomenon Scale (CIPS), and the Work Organization Assessment Questionnaire (WOAQ). Descriptive analyses were complemented by Classification and Regression Trees (CART) to identify predictors of perceived digital preparedness. Results: Most respondents (88%) acknowledged the relevance of digitalization, yet 18% felt unprepared, especially women and administrative staff. Burnout levels were high, with 51% reporting emotional exhaustion, most notably among nurses and female participants. Impostor syndrome affected 43% of the sample, with nurses exhibiting the highest prevalence. CART analysis identified emotional exhaustion, impostor syndrome, and age as principal discriminators of digital preparedness. Conclusions: Our findings highlight the role of emotional exhaustion, impostor syndrome, and age in shaping perceived digital preparedness, underscoring the need for tailored training and supportive practices to ensure a sustainable digital transition. Full article

Hydrogen-assisted fatigue cracking presents a critical challenge to the structural integrity of legacy carbon steel natural gas pipelines being repurposed for hydrogen transport, posing a major barrier to the deployment of hydrogen infrastructure. This study systematically evaluates the fatigue crack growth (FCG) behavior of API 5L X60 pipeline steel under varying hydrogen–natural gas (H₂–NG) blending conditions to assess its suitability for long-term hydrogen service. Experiments are conducted using a custom-designed autoclave to replicate field-relevant environmental conditions. Gas mixtures range from 0% to 100% hydrogen by volume, with tests performed at a constant pressure of 6.9 MPa and a temperature of 25 °C. A fixed loading frequency of 8.8 Hz and load ratio (R) of 0.60 ± 0.1 are applied to simulate operational fatigue loading. The test matrix is designed to capture FCG behavior across a broad range of stress intensity factor values (ΔK), spanning from near-threshold to moderate levels consistent with real-world pipeline pressure fluctuations. The results demonstrate a clear correlation between increasing hydrogen concentration and elevated FCG rates. Notably, at 100% hydrogen, API X60 specimens exhibit crack propagation rates up to two orders of magnitude higher than those in 0% hydrogen (natural gas) conditions, particularly within the Paris regime. In the lower threshold region (ΔK ≈ 10 MPa·√m), the FCG rate (da/dN) increased nonlinearly with hydrogen concentration, indicating early crack activation and reduced crack initiation resistance. In the upper Paris regime (ΔK ≈ 20 MPa·√m), da/dNs remained significantly elevated but exhibited signs of saturation, suggesting a potential limiting effect of hydrogen concentration on crack propagation kinetics. Fatigue life declined substantially with hydrogen addition, decreasing by ~33% at 50% H₂ and more than 55% in pure hydrogen. To complement the experimental investigation and enable predictive capability, a modular machine learning (ML) framework was developed and validated. The framework integrates sequential models for predicting hydrogen-induced reduction of area (RA), fracture toughness (FT), and FCG rate (da/dN), using CatBoost regression algorithms. This approach allows upstream degradation effects to be propagated through nested model layers, enhancing predictive accuracy. The ML models accurately captured nonlinear trends in fatigue behavior across varying hydrogen concentrations and environmental conditions, offering a transferable tool for integrity assessment of hydrogen-compatible pipeline steels. These findings confirm that even low-to-moderate hydrogen blends significantly reduce fatigue resistance, underscoring the importance of data-driven approaches in guiding material selection and infrastructure retrofitting for future hydrogen energy systems. Full article

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease in which environmental factors modulate genetically determined immune dysregulation. Vitamin D has emerged as a plausible modifier of disease expression because its active metabolite signals through the vitamin D receptor on innate and adaptive immune cells and influences antigen presentation, cytokine balance, and lymphocyte differentiation. This narrative review synthesizes current evidence on vitamin D status and supplementation in SLE with attention to organ-specific domains. Observational studies consistently report high rates of hypovitaminosis D in SLE and associations with less favorable clinical profiles, including higher global and renal disease activity, adverse cardiometabolic features, greater infection vulnerability, and neuropsychiatric manifestations. Preclinical models demonstrate neuroprotective and barrier-stabilizing actions of vitamin D analogs, supporting biological plausibility. Interventional trials indicate that supplementation safely corrects deficiency and shows signals of benefit for selected outcomes (e.g., modest activity reductions or fatigue in specific contexts), although effects on interferon signatures, complement, and autoantibodies are heterogeneous and often limited. Overall, current evidence supports optimization of vitamin D status as a low-risk adjunct in comprehensive SLE care while highlighting the need for adequately powered, organ-focused randomized trials using standardized measurements and prespecified endpoints to define causality, therapeutic targets, and long-term safety. Full article

Pipeline anticorrosion patch spray coating is a critical process in pipeline construction and maintenance. It directly affects the adhesion between the pipe exterior and the heat-shrink sleeve and indirectly determines the quality of the coating bond. This study employs ANSYS FLUENT numerical simulations, complemented by on-site automated spray-gun experiments, to systematically investigate the influence of two key parameters—spray distance and gun traverse speed—on coating thickness distribution and uniformity. For both flat and cylindrical specimens, response surface methodology (RSM) applies to construct mathematical deposition models and to optimize process parameters. Simulation results indicate that increasing spray distance leads to edge thinning, while excessive traverse speed causes non-uniform thickness. Optimization improves coating uniformity by 18% on flat specimens and up to 15% on cylindrical specimens. Field validation demonstrates that the optimized process reduces process deviation from the target thickness to within ±10%. At the same time, the maximum relative error between simulation and experiment remains within 13.5%, and the deviation from the standard thickness is 12.25%. These findings provide solid theoretical foundations and practical guidance for automated spray-coating optimization, thereby enhancing the anticorrosion performance of pipeline joints. Full article

Three species of land crab occur in The Bahamas; these are an important source of protein and income for Bahamian islanders. The crab harvesters represent an important and largely untapped knowledge source. We conducted surveys on the Bahamian islands of Andros, New Providence, and Eleuthera to document crabbing practices and catalogue this local ecological knowledge (LEK) of land crabs. The survey primarily employed close-ended questions targeting land crab harvesters; we also recorded general feedback from open-ended questions. Crab collection was primarily for self-consumption. Catch rates varied among islands, and were the highest on Andros. There was a preference for white land crabs (Cardisoma guanhumi) on Andros, whereas on Eleuthera and New Providence, there was no preference for either white or black crabs (Gecarcinus ruricola). The majority of respondents reported a decline in white and black crab numbers, with land development and overharvesting being consistently cited factors. On Andros, forest fires were also reported to account for the loss of crab habitat, whereas on Eleuthera, invasive raccoons were blamed for the population decline. Respondents identified broadleaf forests as critical refuges and food sources for black crabs. Birds were the major predator, confirming findings for other land crab species. Land crabs were not merely a food resource but represented a complex nexus of ecological knowledge, economic systems, cultural traditions, and community practices within Bahamian society. We demonstrated a substantial overlap between traditional and scientific knowledge systems, providing valuable insights into land crab behaviour, habitat use, and ecology that complements formal scientific research. Full article

The conversion of ecological product value is vital for reconciling economic growth with environmental sustainability. As a financial innovation that combines digital technology with inclusive finance, digital finance has emerged as a key driver of this process. Drawing on Chinese provincial panel data from 2011 to 2020, this study shows that digital finance significantly enhances the conversion efficiency of ecological product value (CEEPV), and the results remain robust after addressing endogeneity and sensitivity concerns. The analysis reveals that the depth of use and the level of digitalization of digital finance strongly promote CEEPV, while coverage breadth has no significant effect. Mechanism tests indicate that digital finance improves CEEPV mainly through alleviating rural financing constraints, fostering entrepreneurship, encouraging green innovation, enhancing agricultural social services, and supporting rural e-commerce. In addition, traditional finance and financial regulation complement digital finance in strengthening CEEPV. Heterogeneity analysis further shows that the positive effect of digital finance is concentrated in provinces with higher levels of marketization and urbanization. Overall, the findings underscore the importance of accelerating digital finance development and implementing region-specific policies to maximize its potential in advancing ecological product value realization. Full article