Search Results (21,569)

Background: Artificial intelligence is emerging as a promising tool in surgical oncology, with growing evidence suggesting potential applications in diagnostic support, intraoperative guidance, and perioperative risk assessment. In gastric cancer surgery, emerging applications range from AI-assisted endoscopic detection to data-driven perioperative risk prediction, while some technological developments, particularly in robotic autonomy, derive from broader surgical or experimental models that may inform future gastric procedures. Methods: A narrative review was conducted following established methodological standards, including the Scale for the Assessment of Narrative Review Articles (SANRA) and the Search–Appraisal–Synthesis–Analysis (SALSA) framework. English-language studies indexed in PubMed, Scopus, Embase, and Web of Science up to October 2025 were included. Evidence was synthesized thematically across five domains: AI-assisted anatomical recognition and lymphadenectomy support, autonomous robotic systems, early cancer detection, perioperative predictive and frailty models, and ethical and regulatory considerations. Results: AI-based computer vision and deep learning algorithms have demonstrated promising capabilities for real-time anatomical recognition, surgical phase classification, and intraoperative guidance, although evidence of direct patient-level benefit remains limited. In diagnostic settings, AI-assisted endoscopy and Raman spectroscopy have been shown to improve early lesion detection and reduce dependence on operator experience. Predictive models, including MySurgeryRisk and AI-driven frailty assessments, may support individualized prehabilitation planning and perioperative risk stratification. Persistent limitations include small and heterogeneous datasets, insufficient external validation, and unresolved concerns related to data privacy, algorithmic interpretability, and medico-legal responsibility. Conclusions: Artificial intelligence is progressively emerging as a promising tool in gastric cancer surgery, integrating automation, advanced analytics, and human clinical reasoning. Its safe and ethical adoption requires robust validation, transparent governance, and continuous surgeon oversight. When developed within human-centered and ethically grounded frameworks, AI can augment, rather than replace, surgical expertise, potentially advancing precision, safety, and equity in oncologic care. Full article

Snow accumulation and ice formation can significantly reduce pavement friction, posing a serious threat to traffic safety during winter. Traditional snow-removal methods, including mechanical removal, chemical de-icing agents, and heated pavement systems, suffer from several limitations such as low efficiency, environmental impacts, and high operational costs. Electrically conductive asphalt concrete (ECAC) has therefore emerged as a promising active snow-melting technology. When an electric current passes through the conductive network formed within the asphalt mixture, heat is generated through the Joule heating effect. After incorporating conductive fillers, the electrical resistivity of ECAC mixtures can be reduced from approximately 10⁶–10⁸ Ω·cm for conventional asphalt mixtures to about 10⁻¹–10² Ω·cm. Under an applied voltage typically ranging from 30 to 60 V, ECAC pavements can increase the surface temperature by 10–30 °C within 10–30 min, thereby enabling rapid snow melting and ice removal. Meanwhile, an optimized conductive network can maintain sufficient mechanical performance, with dynamic stability generally exceeding 3000 cycles/mm. When the conductive filler content is reasonably controlled, only a limited reduction in fatigue resistance is observed. This paper presents a comprehensive review of electrically conductive asphalt concrete technologies for snow-melting pavements. The background, underlying mechanisms, material development, system configuration, and field applications of ECAC are systematically summarized. Finally, the current challenges are discussed, including the stability of conductive networks, the trade-off between electrical conductivity and pavement performance, and electrical safety. Future research directions focusing on material optimization, intelligent power control, and long-term field performance evaluation are proposed to support the practical application of ECAC pavements in sustainable winter road maintenance. Full article

Citric acid (CA) necessitates the investigation of the environmental footprint from its production. This study compared three recovery technologies at different readiness levels, industrial calcium hydrogen salt precipitation–ion exchange (CHP-IE), pilot-scale solvent extraction (SE), and laboratory-scale bipolar membrane electrodialysis (BMED), to evaluate the life cycle environmental impacts of CA production when employing each recovery technology. SE and BMED were selected as emerging alternatives, as both are potential candidates to offer environmental or economic advantages over CHP-IE. By modeling the continuous improvement in the key production parameters as cumulative production experience increases, technological learning curves capture the efficiency gains that occur as technologies mature. This study pioneers an integrated ex-ante LCA framework that couples technological learning curves with energy transition scenarios to prospectively compare emerging CA recovery technologies against an industrialized process. Currently, CHP-IE shows the highest profit of 1078 CNY/t CA and the lowest global warming potential (GWP) of 1.79 t CO₂ eq/t CA, with the latter advantage projected to persist until 2030. By 2050, under deep decarbonization, BMED becomes the lowest-carbon option with 0.78 t CO₂ eq/t CA. Furthermore, with maize as the primary raw material, improved cultivation models in Northeast China reduce the environmental impacts of CA production by approximately 3% in acidification potential (AP) and eutrophication potential (EP), while diversified cropping systems in North China yield reductions of over 50% in these two categories. This paper provides an approach of comprehensive evaluation, supporting technology selection and green supply chain development in the CA industry. Full article

Neuroinflammation is a central hallmark of numerous neurological disorders, including Alzheimer’s disease, Parkinson’s disease, traumatic brain injury, and spinal cord damage. Its persistent and dysregulated nature not only accelerates neuronal loss but also impedes endogenous repair, posing a major challenge for effective therapeutic intervention. Recent advances in nanobiotechnology have opened transformative opportunities to modulate neuroinflammation with unprecedented precision while simultaneously supporting neural regeneration. This review highlights emerging nanomaterial-based strategies including lipid-based, polymeric, inorganic nanoparticles designed to traverse the blood–brain barrier (BBB), deliver anti-inflammatory agents, modulate immune cell behavior, and attenuate glial activation. Extending beyond nanoparticle-based delivery systems, recent advances also emphasize the integration of nanomaterials into biomimetic architectures to provide structural and functional cues for neural repair. We further summarize how these functional nanostructured scaffolds, such as extracellular matrix (ECM) mimetic, nanofibrous and conductive hydrogels, are being leveraged in neural tissue engineering to direct stem cell fate, promote axonal outgrowth, and rebuild damaged neuroarchitectures. Moreover, pharmacokinetics, biodistribution, safety, clinical trials, regulatory considerations and limitations of nanotherapeutics in neurodegenerative diseases are discussed. By outlining the current progress, mechanistic insights, and translational challenges, this review underscores the potential of nanobiotechnology-enabled therapeutics to revolutionize the treatment of neuroinflammatory conditions and advance next-generation neural repair technologies. Full article

Global Navigation Satellite Systems (GNSS), benefiting from global coverage, all-weather operation, high precision, and high temporal resolution, have progressively become a key technology in natural hazard monitoring and early warning systems. This paper adopts a hybrid review strategy that integrates scientometric analysis with a systematic review to examine the development trajectory, research hotspots, and technological evolution of GNSS applications in natural hazard studies based on the existing literature. From a technological perspective, three core capabilities of GNSS in hazard monitoring are identified: high-precision, multi-scale deformation sensing; multi-sphere environmental sensing based on signals of opportunity; and real-time monitoring supporting rapid early warning and emergency response. The paper further reviews the development of GNSS in conjunction with multi-sensor collaborative observation and its integration with data-driven methods such as machine learning. Representative applications of GNSS and its integrated techniques are summarized across major hazard types, including earthquakes, tsunamis, landslides, land subsidence, hydrometeorological hazards, and volcanic activity, and further discussions are provided on methodological considerations, the commonalities and differences in GNSS applications across different hazards, and future development directions. The review demonstrates that GNSS applications in natural hazard research are evolving from single-source deformation monitoring toward multi-source integration, intelligent sensing, and operational early warning support systems. This work provides a reference for the further development of GNSS technologies in natural hazard monitoring and risk mitigation. Full article

With the increasing use of modern technologies in interior design, numerous recent studies have made the effects of kinetic-based design techniques on users’ perceptions a crucial topic, and sustainable performance has emerged as essential. From this standpoint, this study uses a space syntax approach to investigate how human behavioral performance in workspaces is affected by kinetic interiors. Three kinetic-based design strategies were employed to evaluate changes in spatial configuration characteristics, and the relevant terminology was adapted to account for the use of kinetic technology. The paper adopts a comparative analysis model to follow these changes using four syntactic measures: integration, choice, connectivity, and clustering coefficient. The proposed evaluation approach is applied to a traditional office building in Port Said, Egypt, showcasing various aspects of kinetic technology in workspaces. The study’s findings elucidate the correlations between design strategies and the resulting spatial characteristics, guiding designers in evaluating the features of each system and facilitating comparisons between them. Finally, the study’s main aim is to propose a three-step design process as a guideline for creating an integrated kinetic technology design, involving the evaluation of the proposed alternatives to achieve the desired spatial characteristics. Full article

This study presents a quantitative, scenario-based framework for analyzing humanity’s potential progression along the Kardashev scale, with emphasis on the transition to Type I (planetary-scale) and Type II (stellar-scale) civilization status. Using humanity as an empirical reference case, we integrate four coupled dimensions of civilizational development: energy utilization, information processing capacity, large-scale construction mass, and population dynamics, modeled through historical data, empirical trends, and physically motivated growth constraints. Energy availability is characterized using global energy production records and insolation statistics for potentially habitable exoplanets, explicitly acknowledging observational biases toward cooler host stars. Information processing growth is constrained by thermodynamic limits and observed trends in global data generation, while construction mass and population evolution are described using exponential and logistic growth models, respectively. These components are combined into a composite Civilization Development Index (CDI), a weighted logarithmic metric designed to track multi-scale civilizational advancement and tested through sensitivity analyses. Under optimistic assumptions of uninterrupted technological growth and absence of civilization-scale catastrophes, the framework suggests that humanity could reach Type I civilization status on the order of the 23rd century, while Type II status represents a substantially longer-term outcome extending into the third millennium or beyond. These timescales should be interpreted as lower bounds, as catastrophic events, sociopolitical constraints, or resource bottlenecks could significantly delay or prevent such transitions. By explicitly delineating assumptions, uncertainties, and physical constraints, this work provides a structured baseline for studies of long-term civilizational trajectories and the factors governing the emergence or absence of advanced technological civilizations. Full article

The escalating global burden of Ulcerative Colitis (UC) underscores the urgent need for novel therapeutic strategies. Although dietary modulation is known to influence UC progression, the specific molecular mediators remain largely undefined. Recently, the G protein coupled receptor 35 (GPR35) has emerged as a promising target for maintaining gut homeostasis and promoting intestinal epithelium repair. Yet, whether the therapeutic benefits of dietary polyphenols are mediated through the direct activation of GPR35 remains unexplored. Here, the NanoLuc Binary Technology (NanoBiT) assay was first used to identify the potential GPR35 agonist from a library of 30 natural polyphenolic compounds. We discovered Ellagic acid (EA), a natural polyphenol abundant in fruits and nuts, as the potent GPR35 agonist owing to its most potent agonistic effect. The dose-dependent effect was further confirmed by both NanoBiT and Bret assay. Then, the binding site of the ligand-receptor complex was predicted via molecular docking, and key interactions were validated by site-directed mutagenesis. The results indicated the key binding site of the complex was Gln93, Arg100, Arg151, Phe163 and Ser262. And the conformation of the complex was verified stable by the molecular dynamics simulation. The bioactivity of EA was then evaluated in vivo. And the in vivo experiment indicated that EA alleviated the symptoms of UC. In addition, complementary in vitro assays, including a wound healing (scratch) assay and an SRB proliferation assay, were employed to investigate its effect on intestinal epithelial repair. The in vitro experiment demonstrated that EA enhanced the migration and proliferation of human colonic epithelial cells, an effect that was specifically abolished by the GPR35 antagonist CID2745687, indicating the key role GPR35 played in the intestinal repair. Collectively, our study demonstrates that the natural polyphenolic compound EA promotes epithelial healing and ameliorates colitis by acting as a GPR35 agonist. Full article

Molecular interactions underpin the functioning of the living cell. Molecules exist in distinct quaternary structural forms, associate with molecular partners in signaling cascades, form transient quinary interactions, localize in membrane domains, and cluster in membrane-less condensates. Measuring the concentration, size, and dynamics of these molecular assemblies remains an enduring biophysical challenge, particularly in cells, where heterogeneity is the rule rather than the exception. Orthogonal signals derived from fluorescence lifetime, fluorescence fluctuations, and fluorescence polarization provide valuable metrics for probing interactions and environments, concentration and size, and rotational dynamics, respectively. This paper combines fluorescence lifetime imaging microscopy with image correlation analysis and polarization to determine the concentrations, brightness, lifetime, and rotational correlation time of different fluorescent states. A two-population model is examined as a prototypical example of a heterogeneous system. The analysis is illustrated on a simple fluorescence model system, where cluster densities, relative brightnesses, lifetimes, and rotational correlation times are extracted. Full article

Background and Objective: Positive surgical margins (PSMs) remain a major challenge during radical prostatectomy, particularly in patients with high-risk prostate cancer (HR-PCa), where extracapsular extension, multifocal disease, and aggressive tumor biology substantially increase the likelihood of incomplete resection. In this setting, PSMs are strongly associated with early biochemical recurrence and frequently prompt adjuvant or salvage treatments, potentially exposing patients to overtreatment and added morbidity. Materials and Methods: To review and critically appraise established and emerging intraoperative technologies for surgical margin assessment during radical prostatectomy, with a specific focus on their potential role and relevance in patients with HR-PCa. Evidence Acquisition: A non-systematic literature review was performed using Pubmed, MEDLINE, Web of Science, and Google Scholar, focusing on preoperative, intraoperative ex vivo, and intraoperative in vivo technologies for margin assessment. Emphasis was placed on techniques with potential applicability to HR-PCa, where real-time intraoperative decision-making is particularly consequential. Evidence Synthesis: Preoperative tools, including multiparametric MRI, PSMA-PET imaging, and predictive nomograms, aid surgical planning but show limited sensitivity for microscopic extracapsular extension, especially in high-risk disease. Intraoperative frozen section analysis reduces positive surgical margin rates while enabling selective nerve-sparing (defined as a side-specific, risk-adapted preservation strategy); however, its widespread adoption is constrained by substantial logistical and resource requirements, and robust oncological outcome data in high-risk populations remain limited. Novel ex vivo approaches, such as fluorescence confocal microscopy and specimen-based PSMA PET/CT imaging, offer rapid whole-gland or targeted margin assessment with reduced dependency on dedicated pathology workflows. In parallel, emerging in vivo technologies, particularly PSMA-targeted near-infrared-fluorescence-guided surgery, enable real-time detection of residual tumor and facilitate selective re-resection, representing a biology-driven approach that may be especially suited to HR-PCa. Conclusions: In high-risk prostate cancer, intraoperative margin assessment technologies may extend beyond functional preservation and play a central role in optimizing oncological radicality and multimodal treatment sequencing. While NeuroSAFE remains the reference standard, PSMA-based ex vivo and in vivo technologies are particularly promising in HR-PCa due to their ability to integrate tumor biology into surgical decision-making. Prospective studies focusing on high-risk-specific oncological and patient-reported outcomes are needed before widespread clinical implementation. Full article

Prostate cancer (PCa) remains a major global health challenge, yet conventional diagnostic methods are often limited by suboptimal accuracy and efficiency. Artificial intelligence (AI) has emerged as a rapidly developing technology capable of integrating multi-source data to enhance clinical decision-making. This narrative review synthesizes current evidence regarding AI applications across key diagnostic domains, including medical imaging, digital pathology, liquid biopsy, and multi-omics integration. Findings indicate that AI models for magnetic resonance imaging (MRI) can improve risk stratification and may reduce unnecessary biopsies in some cohorts, particularly when evaluated alongside structured radiology assessment and clinical variables. In digital pathology, deep learning algorithms have shown high agreement with expert genitourinary pathologists for automated Gleason grading in controlled and externally validated settings, with potential to reduce reporting time for high-volume workflows. Additionally, AI-powered liquid biopsy models may support non-invasive risk stratification, particularly for patients with prostate-specific antigen (PSA) levels in the diagnostic gray zone, while multi-omics integration is being investigated to enhance personalized assessment. Despite advances, challenges regarding data heterogeneity, algorithm interpretability, and workflow integration persist. Future research should prioritize multimodal data fusion, explainable AI development, robust calibration and decision-analytic evaluation, and large-scale prospective validation to standardize protocols and fully realize the potential of AI in precision prostate cancer care. Full article

Strawberry (Fragaria × ananassa Duch.) propagation has evolved significantly over the past 20 years, transitioning from traditional field nursery systems to advanced, controlled, environment production. This review synthesizes recent advances in propagation methods, environmental regulation, and disease management strategies. Traditional field systems face mounting challenges from soilborne pathogens (Neopestalotiopsis species, Phytophthora cactorum, Verticillium dahliae) and regulatory restrictions on methyl bromide fumigation. Plug plant technology offers 80–95% disease reduction and 3–7-week production cycles versus 12–16-weeks traditional cycles, although at higher unit costs. Advanced tray plant systems developed in the Netherlands enable 10–11 months cold storage and programmed year-round production schedules. Elevated bench propagation systems have emerged as dominant commercial technology in East Asian regions, particularly Korea and Japan, where disease pressure necessitated alternatives to conventional nurseries. Micropropagation via temporary immersion bioreactors achieves 50–100% higher multiplication rates, while ensuring virus-free status. Environmental control research reveals complex photoperiod–temperature-chilling interactions regulating dormancy and flowering. Emerging technologies include F₁ hybrid seed propagation and AI-driven automation, achieving 15–25% energy efficiency gains. Despite progress, challenges remain in cost optimization, climate adaptation, and region-specific protocols. This review provides a comparative framework for nursery system selection under evolving climatic and regulatory constraints, identifying critical knowledge gaps and future research priorities for sustainable strawberry propagation. Full article

This study aims to identify and prioritize the key factors influencing export performance among Turkish exporters, based on the resource-based view (RBV) and industrial organization theory (IO), categorizing the factors as internal and external, and employing the Stepwise Weight Assessment Ratio Analysis (SWARA). Twenty-five factors across Internal (IF) and External (EF) categories were evaluated through expert assessments. Results reveal that Internal Factors (58.0%) significantly dominate External Factors (42.0%), indicating that Turkish exporters possess substantial control over their export competitiveness. The top five critical factors are Management and Leadership (9.6%), Strategy (6.2%), Technological Change (5.3%), Industry and Sector Activity (5.0%), and Competitors (5.0%). Surprisingly, traditional factors such as firm size, international experience, and digitalization ranked much lower, challenging conventional assumptions about export success. A leave-one-out (LOO) sensitivity analysis further validated the robustness of these rankings, with Management and Leadership, and Strategy emerging as the most stable and dominant factors across all scenarios. The predominance of management and strategic factors over structural characteristics suggests that even smaller, less experienced companies can achieve export success through effective leadership and strategic planning. These findings contribute theoretically by supporting the notion that the resource-based view has a greater impact on export performance than the industrial organization theory, and they provide practical guidance for companies to focus on managerial and leadership skills, organizational capabilities, and strategic approaches to enhance export investments. The study presents the first comprehensive SWARA-based ranking of export performance factors in the Turkish context, providing empirical evidence to support the internal-external factor debate in the international business literature. Full article

Silicon carbide (SiC) detectors continue to emerge as a promising technology for applications requiring radiation hardness, fast response times, and stable operation in harsh environments. In this work, the charge-collection dynamics of ultra-thin membrane SiC detectors are investigated through time-dependent TCAD simulations, consistent with previously reported measurements. The study analyzes the transient response following the localized generation of electron–hole pairs induced by ions, comparing bulk and membrane detector geometries with identical active-layer thicknesses. Two-dimensional simulations provide a time-resolved characterization of the electron and hole current-density distributions within the active region of the device. The results show that both device architectures present a transient current signal featuring two main components. Despite similarities in the prompt drift-driven signal component, the SiC membrane response is characterized by a short secondary component returning to zero within 3.5 × 10^–10 s at zero external bias, making it well-suited for reliable single-ion detection. In contrast, bulk devices exhibit a markedly different response, characterized by a significantly more intense and prolonged secondary component followed by a long tail that does not return to zero within the simulation time window for all investigated reverse biases. This tail is the result of the collection of carriers generated in the substrate that reach the depletion region through diffusion-driven processes. These findings contribute to the optimization of SiC-based solid-state detectors for quantum-technology device fabrication, demonstrating that the removal of the substrate drastically reduces the diffusion-dominated current component, thereby ensuring precise timing and minimal charge loss. Full article

This review examines the renewed strategic relevance of uranium within the evolving global energy system, emphasizing uranium market dynamics, emerging nuclear technologies, and geopolitical realignments. Moving beyond traditional perspectives that treat uranium primarily as a cyclical commodity or focus narrowly on reactor design, the article frames uranium as a critical strategic resource at the intersection of energy security, decarbonization, and industrial transformation. The analysis integrates market fundamentals with technological developments, particularly small modular reactors (SMRs) and advanced high-temperature reactor systems, and regional policy strategies to provide a holistic perspective largely absent from the existing literature. Quantitative evidence indicates a structurally tightening uranium market, with global reactor demand of approximately 67,500 tU per year and mine production historically meeting only 74–90% of annual requirements. Uranium prices have rebounded from below $20 lb⁻¹ U₃O₈ in 2016 to above $80 lb⁻¹ by late 2023, reflecting supply concentration, long development timelines for new mines, and renewed political commitments to nuclear energy. Demand projections suggest an increase of around 28% by 2030 and the potential for a doubling by mid-century under high-nuclear deployment scenarios. From a technological perspective, while SMRs and advanced reactors may increase uranium consumption per unit of electricity, they substantially expand nuclear energy deployment into new domains, including remote power systems, industrial heat applications, and large-scale low-carbon hydrogen production. Overall, the study highlights a qualitative shift in uranium’s role, positioning it as both a foundational component and a key enabler of integrated low-carbon energy systems spanning electricity, heat, and hydrogen production. Full article