Search Results (936,710)

Background/Objectives: Cutaneous lupus erythematosus (CLE) is a complex autoimmune skin disease driven by genetic predisposition, environmental triggers, and immune dysregulation. Environmental factors such as ultraviolet radiation, smoking, and certain drugs can initiate disease onset by inducing keratinocyte apoptosis. The subsequent release of nucleic acids and danger-associated molecular patterns activates pattern recognition receptors (PRRs) on keratinocytes and immune cells, leading to the production of type I and type III interferons (IFNs) and pro-inflammatory cytokines. The objective of this review is to summarize recent advances in understanding the immunopathogenesis of CLE, with particular attention to emerging cellular players and their therapeutic implications. Methods: A narrative review of the recent literature was performed, including experimental, translational, and clinical studies investigating the cellular and molecular mechanisms underlying CLE and novel targeted treatments derived from these findings. Results: Although plasmacytoid dendritic cells (pDCs) have traditionally been considered the major producers of IFN-I, recent data indicate that pDCs in CLE are functionally impaired and are not the primary source. Other cells, such as keratinocytes have emerged as key producers of IFN-I, contributing to a prelesional, IFN-rich microenvironment. This promotes the recruitment and activation of dendritic cells and other inflammatory myeloid subsets, which are now recognized as central players in amplifying local inflammation. Concurrently, T cells infiltrate the skin, where cytotoxic CD8⁺ T cells attack keratinocytes and CD4⁺ T cells further propagate inflammation via cytokine production. B cells and plasma cells produce autoantibodies, forming immune complexes that perpetuate inflammation. Neutrophils release neutrophil extracellular traps (NETs), exposing autoantigens and further stimulating IFN pathways. Macrophages contribute by presenting autoantigens, producing pro-inflammatory mediators, and failing to effectively clear apoptotic cells and immune complexes. Conclusions: The dynamic interplay between the innate and adaptive immune systems sustains the chronic inflammatory state characteristic of CLE. Based on the pathogenetic novelties, new therapeutic agents targeting specific molecules have been developed, which may improve the treatment of this complex disease in the future. Full article

Introduction: Medical treatment with misoprostol represents one of the main treatments for Early Pregnancy Loss (EPL). In our study, we aimed to identify clinical features associated with a successful response to this approach. Methods: A prospective single-center observational study was conducted at the EPL Clinic of the Department of Obstetrics and Gynecology, Fondazione A. Gemelli IRCCS Rome, Italy. Patients were categorized according to the type of treatment received: spontaneous delivery, elective dilatation and curettage, or medical treatment. A separate analysis was performed within the medical treatment group to distinguish women with a successful response from those with an unsuccessful one. The success of medical treatment was calculated as the response rate (number of patients who successfully responded to treatment/total number of treated patients) with a 95% Confidence Interval (CI). For patients undergoing misoprostol treatment, a multivariable analysis was planned to identify predictors of a successful response, including variables with a p value less than 0.05 in the univariable analysis. Receiver Operating Characteristic (ROC) analysis was performed to evaluate the predictive ability of continuous obstetrics parameters for medical treatment success. The optimal cut-off value to differentiate responsive from unresponsive patients was also determined. The significance level was set at p < 0.05. Results: Sixty-four patients who underwent medical treatment were analyzed. Amenorrhea age was the only parameter inversely associated with treatment success, indicating that an earlier amenorrhea age correlated with a better response to misoprostol. ROC analysis identified a cut-off of 62.5 days, with an AUC (95% CI) of 0.72 (0.55–0.89). An amenorrhea age of ≤ 62.5 days predicted a successful response to medical treatment with a specificity (95% CI) of 90.0% (89.8–90.2) and sensitivity (95% CI) of 54.9% (41.2–68.6). Conclusions: Amenorrhea age emerged as a potential predictor of treatment response in women with EPL undergoing misoprostol therapy. However, further studies of larger sample sizes are needed to validate and improve our model. Full article

Wireless nanosensor networks (WNSNs) are a future technology that will help transform many ideas into reality. Therefore, WNSNs must be properly set up to achieve their intended application goals during the deployment stage. An effective deployment protocol should ensure full coverage of the target area, continuous connectivity between nanosensors, and efficient energy consumption. Since nanosensors are known to have limited energy and computational power, deployment strategies for WNSNs must account for their constrained capabilities and unique properties. In this paper, we review some of existing research on the deployment of WNSNs. Furthermore, we discuss different models that can influence the design of effective deployment strategies for WNSNs. Full article

The trajectory accuracy of equipment with complex motion paths presents a critical engineering challenge. Targeting the precision issues in the operating trajectory of a carbon-free car, this paper proposes an optimization method for complex mechanical trajectories. Firstly, this study investigates gear backlash-induced return error on the steering precision of a carbon-free cam mechanism of cars. Secondly, considering the cumulative return error of gear transmission between gear groups, a comprehensive mathematical model was established to guide the optimization of cam structure. Finally, the steering accuracy before and after optimization is quantitatively evaluated by trajectory calculation. In addition, the optimized structure was tested and compared with the numerical calculation. The experimental and numerical calculation results are highly consistent. The numerical calculation results show that by adjusting the transmission ratio of the gear set and optimizing the cam profile, the cam deflection angle error is reduced by 24.74% and 27.15%, respectively, and the comprehensive cumulative deflection error of the car is significantly reduced by 45.31%. More importantly, the research provides crucial technical support and guidance for achieving precise control and planning complex paths in automated production lines. Full article

Island ecosystems, are characterized by isolation, limited land, and tourism-driven economies, face persistent waste management challenges. Spatial constraints and inadequate infrastructure often limit the development of waste recovery and recycling systems, leading to practices such as open dumping or burning that pose serious environmental and health risks. This paper examines how circular economy (CE) principles, reduce, reuse, recycle, can transform waste into a resource and enhance local resilience. A refined definition of “small islands” is introduced, combining UN criteria with a tourism-intensity filter to capture the strong link between visitor flows and solid waste generation. Barriers to CE adoption are classified into institutional, technical, geographical, financial, and social dimensions, and connected to enabling practices in four thematic areas: multi-stakeholder partnerships, recycling and composting innovations, policy and regulatory tools, and community engagement. Comparative case studies from Europe, Asia, Africa, and the Pacific reveal that integrated approaches are more durable than isolated efforts. Successful initiatives blend technology with governance, education, financial mechanisms, and community participation. The analysis highlights that no single model fits all islands; strategies must be locally adapted to be effective and transferable. Overall, the study shows that circular transitions are both feasible and necessary, offering environmental gains, economic value, and alignment with the EU Green Deal and global sustainability goals. Full article

Background/Objectives: With the rising prevalence of mental health (MH) disorders, improving the effectiveness and quality of MH care has become increasingly imperative. To improve patient care outcomes, it is essential to accurately assess staffing needs and compare outcomes across providers to identify best practices. However, without a robust case-mix adjustment system that accounts for disease severity, efforts to measure staffing requirements and evaluate patient outcomes are of limited value. This study aimed to develop such a system by leveraging a large study population, more clinically homogeneous groups, and advanced modeling techniques. Methods: In this retrospective population-based study, over two million MH patients (n = 2,088,174) were grouped into 162 clinically homogeneous categories using Clinical Classifications Software Refined (CCSR) to enhance predictive accuracy. We evaluated the performance of four statistical models and four artificial intelligence (AI) models to identify the model that delivered the highest predictive power. Results: Among the statistical models, the Box–Cox regression yielded the highest predictive power (R² = 0.42; percent of variation explained [PVE] = 0.300). Among the AI models, CatBoost performed best (R² = 0.458; PVE = 0.311). While the AI models outperformed traditional statistical models, the improvements were modest. Sensitivity analyses confirmed the robustness of these models. Conclusions: Both the Box–Cox and CatBoost models demonstrated superior predictive performance compared to those reported in the literature. These findings suggest that a case-mix system based on either model can be used for risk adjustment to optimize staffing levels and benchmark patient outcomes for quality improvement. Full article

Subconjunctival bleeding in neonatal calves is most commonly seen in association with birth trauma. There are currently no investigations available that examine the systemic causes of this phenomenon. In this prospective and exploratory case–control study, seven out of eighty neonatal calves examined over a two-year period were born with subconjunctival bleeding. The anatomical location of the subconjunctival bleeding and details related to the cow’s and calf’s parturitional and gestational history were recorded. Blood samples from cases and controls (n = 7) were analyzed hematologically, and the serum lysyl oxidase-like enzyme 4 (LOXL4) concentration was determined through an ELISA to establish evidence for possible structural, copper-dependent vascular abnormalities. We found no significant difference in the clinical data of both groups. Hematological examinations revealed no evidence of anemia or thrombocytopenia. Additionally, no significant differences in differential leukocyte counts were observed between the different groups. However, the neutrophil–lymphocyte ratio (NLR) demonstrated a significant difference between the calves with subconjunctival bleeding and controls. The serum LOXL4 protein concentration was not significantly different in calves with subconjunctival bleeding compared to controls. In conclusion, our clinical, hematological, and biochemical data provided no evidence for potential systemic causes of subconjunctival bleeding. However, these results must be considered in light of this study’s small sample size and thus low statistical power. Full article

Chronic low-grade systemic inflammation is increasingly recognized as a key mediator linking stress, pain sensitivity, and cognitive decline. Central to this process are the acute-phase reactants interleukin-6 (IL-6) and C-reactive protein (CRP), which serve as biomarkers of systemic inflammation while promoting neuroimmune dysregulation. Emerging evidence implicates the IL-6–CRP axis in the amplification of pain perception, central sensitization, and stress hypersensitivity, ultimately promoting neurodegenerative processes such as those observed in Alzheimer’s disease (AD) and vascular dementia. Monomeric CRP (mCRP), a proinflammatory isoform generated under mechanical or oxidative stress, can trigger histone modifications (e.g., H3 citrullination), activate endothelial and immune cells, and exacerbate inflammatory pain pathways. These mechanisms are further modulated by genetic and epigenetic factors, including IL-6/CRP/NR3C1 gene variant expression; promoter methylation; and stress-responsive microRNAs, which intersect with dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis, impairing immune resolution and neurocognitive resilience. Psychosocial stressors, such as the burden of caregiving or perfectionistic cognitive patterns, amplify IL-6 and CRP levels, particularly when pain is present, suggesting a synergistic interaction between emotional distress and somatic inflammation. Specifically, elevated CRP is associated with increased pain sensitivity, lower pain thresholds, and cognitive decline even in subclinical populations, providing a feedforward model in which chronic stress and pain potentiate systemic inflammation, disrupt neuroendocrine feedback, and accelerate neurodegenerative pathology. However, in this model, the potentially critical mechanistic and pathological role of mCRP remains to be discovered. This review addresses the missing elements of these overlapping pathways and discusses the therapeutic potential of targeting IL-6–CRP signaling, stress regulation, and epigenetic modifiers as strategies to ameliorate inflammation-driven cognitive decline and enhance stress resistance in chronic disease contexts. We propose that plasma mCRP or more likely the isoform-aware metric, the mCRP/CRP ratio, will provide a biologically anchored, potentially more discriminative approach to vascular-neuroimmune risk and capture the propensity for local effector signaling, likely outperforming hs-CRP or IL-6 alone for risk stratification across neurovascular and stress-sensitized pain phenotypes. Full article

As urbanization accelerates, façade defects in existing residential buildings have become increasingly prominent, posing serious threats to structural safety and residents’ quality of life. In the high-density built environment of Shenzhen, traditional manual inspection methods exhibit low efficiency and high susceptibility to omission errors. This study proposes an integrated framework for façade defect detection that combines unmanned aerial vehicle (UAV)-based visible-light and thermal infrared imaging with deep learning algorithms and parametric three-dimensional (3D) visualization. Three representative residential communities constructed between 1988 and 2010 in Shenzhen were selected as case studies. The main findings are as follows: (1) the fusion of visible and thermal infrared images enables the synergistic identification of cracks and moisture intrusion defects; (2) shooting distance significantly affects mapping efficiency and accuracy—for low-rise buildings, 5–10 m close-range imaging ensures high mapping precision, whereas for high-rise structures, medium-range imaging at approximately 20–25 m achieves the optimal balance between detection efficiency, accuracy, and dual-defect recognition capability; (3) the developed Grasshopper-integrated mapping tool enables real-time 3D visualization and parametric analysis of defect information. The Knet-based model achieves an mIoU of 87.86% for crack detection and 79.05% for leakage detection. This UAV-based automated inspection framework is particularly suitable for densely populated urban districts and large-scale residential areas, providing an efficient technical solution for city-wide building safety management. This framework provides a solid foundation for the development of automated building maintenance systems and facilitates their integration into future smart city infrastructures. Full article

Protein instability leading to haze formation remains a critical challenge in white wine production. For more than a century, bentonite has been the most widely adopted solution due to its effectiveness and efficiency. However, its use poses several drawbacks, including non-specific adsorption of desirable compounds potentially affecting wine quality, wine losses, environmental impact, and health and safety risks for operators. These limitations have spurred extensive research to understand the mechanisms underlying protein instability and to identify alternative stabilization strategies. This review provides a comprehensive analysis of bentonite’s role in white wine protein stabilization, examining its physicochemical properties, treatment variables, and interactions with wine components. Particular attention is given to predictive tests aimed at optimizing dosage, as well as to bentonite’s impact on volatile organic compounds, phenolics, and elemental composition. Furthermore, emerging alternatives and knowledge gaps are discussed to outline future directions toward sustainable and efficient stabilization practices. This synthesis aims to support both scientific advancement and practical applications for the wine industry. Full article

This paper considers the question of local dynamics of the simplest non-periodic chains of nonlinear first-order equations with two-sided couplings. The main attention is paid to the study of chains with a large number N of elements. The critical cases in the problem of stability of the zero equilibrium state are identified. Questions about bifurcations of regular and irregular solutions are considered. Analogues of normal forms are constructed, the so-called quasinormal forms, which are special nonlinear equations of parabolic type. Their nonlocal dynamics determine the local structure of solutions to the original problem. Bifurcation problems for quasinormal forms are considered, and interestingly, the boundary conditions for them are not classical. The asymptotics of both regular and irregular solutions are constructed. The latter have the most complex structure. In particular, for negative values of the coupling parameter between elements, continual families of equilibrium states, cycles, and more complex structures can arise in the chain. Full article

Penetration of harmful substances, such as chloride ions, is a major contributor to durability issues in concrete structures. Low permeability is critical for long-term performance, prompting the assessment and classification of concrete based on its resistance to ionic transport. However, the transport mechanisms are complicated and influenced by a range of interdependent factors including binder type, mixture proportions, specimen age, and curing conditions. There are two widely adopted test methods used for assessing chloride ion permeability: the Rapid Chloride Permeability Test (RCPT) and the Surface Resistivity Test (SRT), a non-destructive alternative. While RCPT is well-established, its long testing time as well as its high costs and sensitivity to specimen preparation limit its practicality. The SRT offers faster, more repeatable, and easier implementation. This state-of-the-art review systematically compares RCPT and SRT results across studies, revealing a strong inverse correlation with coefficients of determination (R²) from 0.85 to 0.95, as influenced by compressive strength, testing age, water-to-cement ratio, and supplementary cementitious material (SCM) type. Results showed that RCPT often has standard deviation (SD) values exceeding 300 coulombs and coefficient of variation (COV) values up to 10%, while SRT has lower variability (SD < 3 kΩ·cm and COV ≈ 5%). The review concludes that, with appropriate calibration, the SRT can reliably classify concrete permeability, closely aligning with RCPT results. However, research gaps remain regarding the applicability of existing models to less conventional SCMs and concrete types. Future research should prioritize the development of binder-specific correlations, validation using diffusion-based methods, and exploration of alternative SCMs and curing regimens to expand SRT applicability. Full article

The wake characteristics of tidal turbines are significantly influenced by turbulence intensity (TI) and flow velocity in the marine environment. This study employs the Blade Element Momentum (BEM)–CFD method to model two-bladed horizontal tidal turbine wakes, simplifying the turbine geometry while ensuring computational efficiency. The numerical model, validated against experimental data, demonstrates reliable accuracy. Simulations were conducted for background TI levels of 2%, 6%, 10%, 14%, and 18%. Results indicate that wake regions initially expand and then contract, with the contraction point moving closer to the turbine as TI increases. At 2% TI, the wake influence region extends to an axial distance/diameter (X/D) ratio of 20, while at 18% TI, contraction begins at X/D = 4. Low TI results in more extensive low-speed regions, whereas high TI accelerates wake recovery. As TI increases, the wake’s turbulence rapidly blends with the background, leading to a reduction in turbulence increments within the wake. Additionally, an analytical wake model for tidal turbines was developed, incorporating turbulence intensity into the formula. The predicted curve exhibited good agreement with the CFD data. This model enables a quick and efficient prediction of wake velocity changes under varying turbulence intensities. Full article

Oral health represents a complex interplay between local microbial ecology, host immune responses, and systemic physiology. Far from being an isolated entity, the oral cavity is the entry point of the gastrointestinal and respiratory tracts and harbors up to one trillion microorganisms. While commensal species maintain ecological balance, pathogenic bacteria such as Porphyromonas gingivalis drive inflammatory conditions like gingivitis and periodontitis. Studies suggest that as chronic inflammation persists and is manifested through sustained breakdown of periodontal tissues, systemic dissemination of oral pathogens contributes to bacteremia, endothelial dysfunction, and neuroinflammation. As a result, increasing evidence has been found linking these oral pathogens and inflammatory mediators to systemic conditions including Alzheimer’s disease, cardiovascular disease, and arthritis. This narrative review synthesizes current evidence linking oral health to systemic disease while addressing practical strategies to strengthen preventive care. Evidence-based interventions are presented as accessible tools for reducing both oral and systemic inflammatory burden. Importantly, this article emphasizes the public health imperative of bridging mechanistic insights with actionable oral hygiene practices. By promoting evidence-based strategies such as scaling and root planing, dietary sugar reduction, and judicious use of antimicrobial agents, individuals may reduce their risk of chronic inflammatory and degenerative diseases. Future interdisciplinary research is needed to clarify causal mechanisms and optimize preventive frameworks integrating oral-systemic health. Full article

An effective approach to maintaining uninterrupted coolant flow in heat supply systems—and thereby reducing energy consumption—is to prevent the formation of corrosion-scale deposits on the inner surfaces of metal pipes. This is typically achieved by performing anti-corrosion treatment on the coolant. However, the efficiency of this method depends on several factors, including pipe conditions, water flow rate, and water composition. To inhibit corrosion and scale formation on the internal surfaces of pipelines, specific inhibitors are used to create protective films on the metal surface. For strong adhesion of these films, preliminary chemical cleaning of the metal surface with low-concentration acid solutions is essential. This cleaning is usually performed in circulation mode for several hours. The activated surface enhances inhibitor adhesion, leading to the formation of films with improved protective properties. The quality of the anticorrosive films was evaluated using a JSM-6490LV scanning electron microscope equipped with INCAEnergy energy-dispersive microanalysis systems, HKL-Basic structural analysis, ContrAA-300 atomic adsorption spectrometer, and potentiostat IPC-Pro MF. Full article