Search Results (253)

Sepsis and cancer, though distinct in their clinical manifestations, share profound pathophysiological overlaps that underscore their interconnectedness in disease progression and outcomes. Here we discuss the intricate biological mechanisms linking these two conditions, focusing on the roles of inflammation, immune dysregulation, and metabolic alterations. In sepsis, an uncontrolled immune response to infection leads to a cytokine storm, tissue damage, and immune paralysis, while cancer exploits chronic inflammation and immunosuppressive pathways to promote tumor growth and metastasis. Both conditions exhibit metabolic reprogramming, such as the Warburg effect in cancer and glycolysis-driven immune cell activation in sepsis, which fuels disease progression and complicates treatment. Sepsis can exacerbate cancer progression by inducing genomic instability, epigenetic modifications, and a pro-tumorigenic microenvironment, while cancer increases susceptibility to sepsis through immunosuppression and treatment-related complications. The shared pathways between sepsis and cancer present unique opportunities for therapeutic intervention, including anti-inflammatory agents, immune checkpoint inhibitors, and metabolic modulators. Anti-inflammatory therapies, such as IL-6 and TNF-α inhibitors, show promise in mitigating inflammation, while immune checkpoint inhibitors like anti-PD-1 and anti-CTLA-4 antibodies are being explored to restore immune function in sepsis and enhance antitumor immunity in cancer. Metabolic modulators, including glycolysis and glutaminolysis inhibitors, target the metabolic reprogramming common to both conditions, though their dual roles in normal and pathological processes necessitate careful consideration. Additionally, antimicrobial peptides (AMPs) represent a versatile therapeutic option with their dual antimicrobial and antitumor properties. In this review, we also highlight the critical need for integrated approaches to understanding and managing the complex interactions between sepsis and cancer. By bridging the gap between sepsis and cancer research, this work aims to inspire interdisciplinary collaboration and advance the development of targeted therapies that address the shared mechanisms driving these devastating diseases. Ultimately, these insights may pave the way for novel diagnostic tools and therapeutic strategies to improve outcomes for patients affected by both conditions. Full article

This article introduces a high-efficiency, high-voltage-ratio bidirectional DC–DC converter based on the Dual-Active-Bridge (DAB) topology, specifically designed for applications involving low-voltage, high-capacity cells. Addressing the critical challenge of enhancing bidirectional power transfer efficiency under ultra-high step-up ratios, which is essential for integrating renewable energy sources and battery storage systems into modern power grids, an optimized control strategy is proposed. This strategy focuses on refining switching patterns and minimizing conduction losses to improve overall system efficiency. Theoretical analysis revealed significant enhancements in efficiency across various operating conditions. Simulation results further confirmed that the converter achieved exceptional performance in terms of efficiency at extremely high voltage conversion ratios, showcasing full-range Zero-Voltage Switching (ZVS) capabilities and reduced circulating reactive power. Specifically, the proposed method reduced circulating reactive power by up to 22.4% compared to conventional fixed-frequency control strategies, while achieving over 35% overload capability. These advancements reinforce the role of DAB as a key topology for next-generation high-performance power conversion systems, facilitating more efficient integration of renewable energy and energy storage solutions, and thereby contributing to the stability and sustainability of contemporary energy systems. Full article

This article proposes a high-efficiency isolated three-port resonant converter for DC microgrids, combining a dual active bridge (DAB)–LLC topology with hybrid Pulse Width Modulat-Pulse Frequency Modulation (PWM-PFM) phase shift control. Specifically, the integration of a dual active bridge and LLC resonant structure with interleaved buck/boost stages eliminates cascaded conversion losses. Energy flows bidirectionally between ports via zero-voltage switching, achieving a 97.2% efficiency across 150–300 V input ranges, which is a 15% improvement over conventional cascaded designs. Also, an improved PWM-PFM shift control scheme dynamically allocates power between ports without altering switching frequency. By decoupling power regulation and leveraging resonant tank optimization, this strategy reduces control complexity while maintaining a ±2.5% voltage ripple under 20% load transients. Additionally, a switch-controlled capacitor network and frequency tuning enable resonant parameter adjustment, achieving a 1:2 voltage gain range without auxiliary circuits. It reduces cost penalties compared to dual-transformer solutions, making the topology viable for heterogeneous DC microgrids. Based on a detailed theoretical analysis, simulation and experimental results verify the effectiveness of the proposed concept. Full article

Rocky desertification, a severe form of land degradation in tropical and subtropical regions driven by vegetation loss and soil erosion, poses significant ecological and economic challenges. Field trials in Fengshan County, Guangxi, China, evaluated the efficacy of NPK compound fertilizers, slow-release fertilizers, and bio-organic fertilizers on soil rehabilitation, microbial diversity, and the growth of Mahonia fortunei, a key species for ecological restoration and understory cash crop cultivation. The results demonstrated the bio-organic fertilizer’s superiority in soil regeneration, increasing organic matter by 30.4% (Bolin), 15.73% (Longlai), and 21.83% (Longlei) compared to NPK compound fertilizers, alongside elevating the total nitrogen (reaching 19.4 g/kg in Bolin) and phosphorus (85.45% higher in Bolin). Bio-organic fertilizer increased enzyme activities by 27–202% and enhanced microbial diversity, notably Proteobacteria and Actinobacteria. Slow-release fertilizers maximized micronutrient availability (e.g., Cu increased by 151.65% in Bolin) and improved plant growth, achieving peak Mahonia fortunei (Lindl.) Fedde height (3.62 cm, increasing 9.04%) and ground diameter (4.5 cm, increasing 18.42%) in Longlei compared to NPK compound fertilizers. Regional variability highlighted the bio-organic fertilizer’s dominance in soil fertility metrics, while slow-release formulations excelled in micronutrient enrichment and plant performance. NPK compound fertilizers exhibited the lowest efficacy, potentially exacerbating soil degradation. This study advocates integrating bio-organic fertilizers for soil regeneration with targeted slow-release applications for crop productivity, particularly in understory cash crop systems. Such a dual approach bridges ecological restoration with economic resilience in karst ecosystems, offering scalable solutions for global rocky desertification mitigation. Full article

Non-EU international students encounter considerable challenges in social integration, cultural adaptation, and emotional well-being within UK higher education. Despite this, the role of internet memes as a form of participatory digital media in mediating these experiences has not been extensively studied. This paper examines how non-EU students at a British university utilise memes to manage cross-cultural identity and daily stressors. Employing an Experience-Centred Design (ECD) approach, our qualitative research involved 20 participants through digital cultural probes, semi-structured interviews, and co-design workshop. We discovered that memes serve a dual role: they provide emotional bridges that foster a sense of belonging through shared humour, yet they also risk exclusion due to cultural opacity. We introduce the concept of “negotiated humour”, which requires cross-cultural explanation and reduces comedic spontaneity but enhances intercultural understanding. Furthermore, we identify a continuum of meme usage that reflects different phases of acculturation, ranging from expressing frustrations to creating hybrid cultural expressions. This study contributes to cross-cultural adaptation theory by highlighting memes as boundary objects in identity negotiation. We suggest design implications for culturally sensitive platforms, such as contextual footnotes, and institutional interventions like meme-based orientation activities to exploit humour’s potential for fostering inclusive dialogue. Our research highlights how transient digital humour can provide deep insights into identity, community, and the complex dynamics of cross-cultural adaptation. Full article

Soil heavy metal contamination poses critical challenges to ecological sustainability in mining regions, particularly in acidic soils from copper sulfide mines. This study developed a sustainable remediation strategy using a carbonyl iron powder–biochar composite (CIP@BC) derived from agricultural waste (rice husk) and industrial byproducts. The composite was synthesized through an energy-efficient mechanical grinding method at a 10:1 mass ratio of biochar to carbonyl iron powder, aligning with circular economy principles. Material characterization revealed CIP particles uniformly embedded within biochar’s porous structure, synergistically enhancing surface functionality and redox activity. CIP@BC demonstrated exceptional Cu²⁺ immobilization capacity (910.5 mg·g⁻¹), achieved through chemisorption and monolayer adsorption mechanisms. Notably, the remediation process concurrently improved key soil health parameters. Soil incubation trials demonstrated that 6% CIP@BC application elevated soil pH from 4.27 to 6.19, reduced total Cu content by 29.43%, and decreased DTPA-extractable Cu by 67.26%. This treatment effectively transformed Cu speciation from bioavailable to residual fractions. Concurrent improvements in electrical conductivity (EC), cation exchange capacity (CEC), soil organic matter (OM), and soil water content (SWC) collectively highlighted the composite’s multifunctional remediation potential. This study bridges environmental remediation with sustainable land management through an innovative waste-to-resource approach that remediates acidic mine soils. The dual functionality of CIP@BC in contaminant immobilization and soil quality restoration provides a scalable solution. Full article

Electric Vehicles (EV) significantly contribute to reducing carbon emissions and promoting sustainable transportation. Among EV technologies, hybrid energy storage systems (HESS), which combine fuel cells, power batteries, and supercapacitors, have been widely adopted to enhance energy density, power density, and system efficiency. Bidirectional DC-DC converters are pivotal in HESS, enabling efficient energy management, voltage matching, and bidirectional energy flow between storage devices and vehicle systems. This paper provides a comprehensive review of bidirectional DC-DC converter topologies for EV applications, which focuses on both non-isolated and isolated designs. Non-isolated topologies, such as Buck-Boost, Ćuk, and interleaved converters, are featured for their simplicity, efficiency, and compactness. Isolated topologies, such as dual active bridge (DAB) and push-pull converters, are featured for their high voltage gain and electrical isolation. An evaluation framework is proposed, incorporating key performance metrics such as voltage stress, current stress, power density, and switching frequency. The results highlight the strengths and limitations of various converter topologies, offering insights into their optimization for EV applications. Future research directions include integrating wide-bandgap devices, advanced control strategies, and novel topologies to address challenges such as wide voltage gain, high efficiency, and compact design. This work underscores the critical role of bidirectional DC-DC converters in advancing energy-efficient and sustainable EV technologies. Full article

Host metabolic reprogramming is a critical strategy employed by many viruses to support their replication, and the key metabolic enzyme plays important roles in virus infection. This study investigates the role of pyruvate kinase M2 (PKM2), a glycolytic enzyme with non-canonical functions, in the replication of classical swine fever virus (CSFV). Using PK-15 cells and piglet models, we demonstrate that CSFV infection upregulates PKM2 expression both in vitro and in vivo, creating a proviral environment. knockdown of PKM2 by siRNA reduced CSFV proliferation, while PKM2 overexpression significantly increased virus propagation, which was evaluated by viral protein synthesis, genome replication, and progeny virion production. A direct interaction between PKM2 and CSFV NS5B protein was identified by co-immunoprecipitation and GST-pulldown assays, and PKM2 affected NS5B polymerase activity in a dual-luciferase reporter assay, with PKM2 depletion reducing RdRp function by 50%. Temporal analysis of the first viral replication cycle confirmed PKM2-dependent enhancement of CSFV RNA synthesis. These findings establish PKM2 as a proviral host factor that directly binds NS5B to potentiate RdRp activity, thereby bridging metabolic adaptation and viral genome replication. This study provides new evidence of a glycolytic enzyme physically interacting and enhancing viral polymerase function, offering new information about CSFV–host interaction. Full article

This work introduces a novel battery charger implemented with a four-level three-phase neutral-point-clamped converter and a four-level single-phase dual-active-bridge converter, which offers the intrinsic advantages of multilevel conversion, provides galvanic isolation and allows bidirectional power flow. A detailed and extensive modeling of the system is developed, together with the design of appropriate closed-loop control and modulation. The proposed system allows individual charging of each battery pack, ensuring that the full capacity of the battery bank is utilized, even when the battery packs have different state-of-charge levels, differ in nominal capacities, or use different chemistries. Furthermore, the proposed control system manages the overall DC-link voltage and ensures voltage balance across both DC-links in the system. The effectiveness of the proposed system configuration and control has been validated through simulations. The simulation results show good dynamic response in different operating scenarios, confirming the suitability, feasibility, and benefits of the proposed implementation and control approach. Full article

Cyclin-dependent kinase 1 (CDK1) has emerged as a critical regulator of cell cycle progression, yet its role in liver fibrosis-associated hepatocellular carcinoma (LF-HCC) remains underexplored. This study aimed to systematically evaluate CDK1’s prognostic significance, immune regulatory functions, and therapeutic potential in LF-HCC pathogenesis. Integrated bioinformatics approaches were applied to multi-omics datasets from GEO, TCGA, and TIMER databases. Differentially expressed genes were identified through enrichment analysis and protein–protein interaction networks. Survival outcomes were assessed via Kaplan–Meier analysis, while immune cell infiltration patterns were quantified using CIBERSORT. Molecular docking simulations evaluated CDK1’s binding affinity with pharmacologically active compounds (alvocidib, seliciclib, alsterpaullone) using AutoDock Vina. CDK1 demonstrated significant overexpression in LF-HCC tissues compared to normal controls (p < 0.001). Elevated CDK1 expression correlated with reduced overall survival (HR = 2.41, 95% CI:1.78–3.26, p = 0.003) and advanced tumor staging (p = 0.007). Immune profiling revealed strong associations between CDK1 levels and immunosuppressive cell infiltration, particularly regulatory T cells (r = 0.63, p = 0.001) and myeloid-derived suppressor cells (r = 0.58, p = 0.004). Molecular docking confirmed high-affinity binding of CDK1 to kinase inhibitors through conserved hydrogen-bond interactions (binding energy ≤ −8.5 kcal/mol), with alvocidib showing optimal binding stability. This multimodal analysis establishes CDK1 as both a prognostic biomarker and immunomodulatory regulator in LF-HCC pathogenesis. The enzyme’s dual role in driving tumor progression and reshaping the immune microenvironment positions it as a promising therapeutic target. Computational validation of CDK1 inhibitors provides a rational basis for developing precision therapies against LF-HCC, bridging translational gaps between biomarker discovery and clinical application. Full article

Photoacoustic imaging (PAI) has emerged as a transformative modality for bridging traditional Chinese medicine (TCM) theory and contemporary biomedical research in acupuncture mechanism studies. This review assesses PAI’s capacity to decode acupuncture-induced neuromodulatory and hemodynamic effects, with dual focus on the central nervous system (CNS) responses and acupoint-specific microcirculatory dynamics. Leveraging the photoacoustic effect coupled with ultrasonic detection, PAI enables non-invasive, high-resolution mapping of cerebral hemodynamic parameters, including blood flow, oxygen saturation and hemoglobin concentrations, in real time. Experimental evidence from murine models of cerebral hypoperfusion and ischemic stroke demonstrates acupoint-specific spatiotemporal activation patterns, particularly at Yongquan (KI1) and Yanglingquan (GB34), revealing cortical hemodynamic reorganization and angiogenesis. At the microcirculatory level, PAI identifies functional transitions from quiescent to activated vascular states during disease progression, characterized by altered perfusion dynamics and vascular permeability. While structural metrics (e.g., microvascular density and curvature) show no significant differences in knee osteoarthritis models, functional parameters such as hemoglobin flux and oxygen metabolism emerge as critical biomarkers of acupoint specificity. PAI further enhances treatment precision through standardized acupoint localization, as evidenced by electrostimulation studies at Hegu (LI4) and Zhongwan (CV12). This synthesis highlights PAI’s dual contributions: (1) validating CNS-mediated systemic regulation via acupoint-brain functional correlations, and (2) providing multimodal quantification of microcirculatory dynamics. Future directions emphasize integration of molecular probes for neuroendocrine pathway visualization and multimodal imaging to address unresolved thermal/optical interactions. By synergizing TCM principles with advanced biophotonics, PAI establishes a paradigm for mechanistic acupuncture research and clinical translation. Full article

This paper provides guidelines for designing and modeling sensing coils in high-voltage, high-frequency transformers to enable a cost-efficient design of isolated converter topologies. The objective is to design a magnetic structure in which an additional sensing coil, placed on the main transformer, can be used to precisely measure the voltage on the secondary, despite fast changes in the voltage and current. This is usually a challenging task since high-voltage transformers will always require considerable isolation, which will give rise to significant leakage fields, which in turn will distort the measurement, especially at high frequencies. Our main finding is that this problem can be avoided if the sensing winding is carefully routed to maintain a certain ratio between the transformer’s coupling coefficients, which is achieved by placing this winding in an area within the core in which the magnetic field is low. In principle, this leads to a linear relationship between the voltages of the secondary and sensing windings despite non-ideal leakage inductances. The results are demonstrated experimentally using a 10 kW transformer, with 60 kV isolation, demonstrating a coupling coefficient of about 0.99, which reflects an error of less than $1.5\%$ in the sensed secondary voltage. Full article

The conventional model predictive control (MPC) for dual active bridge (DAB) converters relies heavily on the accuracy of system parameters. To address this issue, this paper proposes a model predictive voltage control strategy for DAB based on a super-twisting integral sliding mode observer (STISMO). By reducing the system parameter sensitivity and incorporating a disturbance compensation mechanism, the proposed strategy enhances robustness while preserving the dynamic response advantages of MPC. Firstly, an ultra-local model of the DAB converter is constructed to reduce dependence on system parameters. Secondly, a STISMO with an integral sliding surface is designed to achieve rapid and accurate estimation of unmodeled dynamics and disturbances in the ultra-local model, along with real-time compensation. The finite-time convergence of observation errors is rigorously proven via Lyapunov stability theory. Subsequently, a two-step prediction model combined with rolling optimization of the cost function is employed to solve for the optimal phase-shift angle, which is then applied in the next control cycle. Finally, experimental validation was conducted through a DAB converter test platform, demonstrating the effectiveness of the proposed method in enhancing system robustness and dynamic performance. Full article

Chronic pain, defined by persistent pain beyond normal healing time, is a pervasive and debilitating condition affecting up to 30–50% of adults globally. In parallel, neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS) are characterized by progressive neuronal loss and cognitive or motor decline, often underpinned by pathological protein misfolding and aggregation. Emerging evidence suggests a potential mechanistic link between chronic pain and NDs, with persistent pain contributing to neuroinflammatory states and protein homeostasis disturbances that mirror processes in neurodegeneration. This review explores the hypothesis that protein misfolding and aggregation serve as a mechanistic bridge between chronic pain and neurodegeneration. We systematically examine molecular pathways of protein misfolding, proteostasis dysfunction in chronic pain, and shared neuroimmune mechanisms, highlighting prion-like propagation of misfolded proteins, chronic neuroinflammation, and oxidative stress as common denominators. We further discuss evidence from experimental models and clinical studies linking chronic pain to accelerated neurodegenerative pathology—including tau accumulation, amyloid dysregulation, and microglial activation—and consider how these insights open avenues for novel therapeutics. Targeting protein aggregation, enhancing chaperone function, modulating the unfolded protein response (UPR), and attenuating glial activation are explored as potential strategies to mitigate chronic pain and possibly slow neurodegeneration. Understanding this intersection not only elucidates chronic pain’s role in cognitive decline but also suggests that interventions addressing proteostasis and inflammation could yield dual benefits in pain management and neurodegenerative disease modification. Full article

This research aims at examining the progress of retail demand forecasting and customer classification via regression models and RFM analysis in the retail chain industry. Entailing actual retail sales data, this work utilizes three regression models:—MLP Regressor, Ridge Regressor, and KNN Regressor to forecast sales. Of them, the MLP Regressor yielded the least Mean Squared Error (MSE = 2.66 × 10) and the best coefficient of determination (R² = 0.9398) stressing its ability to identify deviations from linearity in the sales data. Also, RFM analysis, augmented by K-Means clustering, successfully categorized customers into actionable segments: loyal customers, champions, at-risk, and hibernating. Exploratory data analysis (EDA) findings indicated dramatic changes in sales and revenue, activities, and customer interactions, and products. The combined application of these approaches offers operational solutions in product acquisition, marketing communication, and revenue enhancement. The study advances current research by integrating predictive regression models with RFM segmentation, offering a dual-framework that enhances retail demand forecasting and customer behavior analysis, thereby bridging a critical gap in data-driven decision-making. However, bearing in mind that the lack of demographic data and limited feature variety may constrain the model’s ability to capture personalized customer behaviors, the findings provide a foundation for integrating more diverse datasets and advanced learning approaches for improved retail analytics. Full article