Search Results (6,514)

Background/Objectives: Glioblastoma (GBM) remains the most aggressive primary brain tumor in adults, characterized by inevitable recurrence, extensive inter-and intratumoral heterogeneity, and resistance to current therapies. A defining feature of GBM is the dynamic interplay between malignant cells and a diverse tumor microenvironment (TME), which together drive disease progression, therapeutic adaptation, and relapse. Understanding these complex cellular ecosystems has therefore become a major focus of glioblastoma research. Recent advances in spatial omics technologies have transformed our ability to investigate GBM biology directly within intact tissue architectures. Over the past five years, an expanding array of spatial transcriptomic, proteomic, and multi-omic platforms has enabled high-dimensional characterization of cellular states, cell–cell interactions, and tissue niches while preserving spatial context. These approaches have generated unprecedented insights into tumor organization, cellular plasticity, immune landscapes, vascular niches, and treatment-induced ecosystem remodeling. Methods: In this review, we provide an overview of spatial omics applications in glioblastoma research so far. Results: We summarize the technologies employed, the types and numbers of patient samples analyzed, and the major biological and clinical insights generated. We compare the strengths and limitations of different spatial platforms, discuss key considerations for study design and data interpretation, and highlight emerging trends in multimodal and longitudinal analyses. Conclusions: By integrating both technological and biological perspectives, this review serves as a practical resource for researchers seeking to implement spatial omics approaches in glioblastoma studies and to advance precision neuro-oncology. Full article

Background: Ischemic stroke remains a leading cause of mortality and long-term disability worldwide, with complex and heterogeneous pathophysiological processes. Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) has been increasingly applied to investigate cellular heterogeneity at high resolutions. Methods: We systematically searched PubMed, Web of Science, and Embase to identify studies that applied sc/snRNA-seq in ischemic stroke research. Based on the retrieved literature, we summarized the bioinformatic analytical methods and application strategies reported in these studies, focusing on how sc/snRNA-seq has been utilized across different research contexts. Results: The application of sc/snRNA-seq in ischemic stroke has expanded rapidly across species and sample types. A wide range of downstream bioinformatic analyses have been employed, including clustering, differential expression analysis, trajectory inference, gene regulatory network analysis, and cell–cell communication analysis. These approaches have been applied to investigate diverse biological processes in ischemic stroke. In addition, these analytical strategies have been extended to multiple biological contexts, including extracerebral tissues, stroke-related modifiers, and their associated complications. Furthermore, integrative analytical approaches that combine multiple datasets, bulk transcriptomics, and other omics data have been increasingly utilized. Advances in temporal and spatial resolutions have enabled analyses across different stages and anatomical regions. Conclusions: This review systematically summarizes the analytical methods and application strategies of sc/snRNA-seq in ischemic stroke. These approaches provide a structured perspective for understanding the application of single-cell technologies in this field. Future studies may benefit from standardized designs and coordinated analytical strategies to facilitate more systematic investigations. Full article

IoT cloud platforms support the monitoring and management of distributed renewable-energy systems, but sustaining them can be challenging in academic and community initiatives with limited resources. Recurring cloud-service fees, dependence on proprietary platforms, and limited local control may become major obstacles, particularly when long-term service operation must be combined with technical capacity-building within local institutions and surrounding communities. This paper presents an open-source, multi-tenant IoT cloud architecture developed within the GREATER Erasmus+ framework and deployed in renewable-energy Living Labs in Rwanda. The architecture is built using widely adopted open-source tools, including Docker, Node-RED, MySQL, Nginx, MQTT, and HTTPS APIs. The main novelty is an open-source middleware layer that transforms standard components into a shared, tenant-aware platform by coordinating authentication, role-based access, tenant-aware routing, controlled database access, separate Node-RED workspaces, and dashboard visibility for different Living Labs and user roles. The platform has been deployed in real settings, supporting photovoltaic monitoring, solar-powered irrigation, community energy services, domestic energy monitoring, and educational activities. The platform is evaluated in terms of cost, resource usage, communication delay, reliability mechanisms, and access-control behavior. The results show that heterogeneous IoT services can be hosted on modest local infrastructure while maintaining logical separation between Living Lab data and services. By combining open-source technologies, multi-tenant management, and field deployment, the proposed architecture offers a practical model for higher-education institutions and community-oriented renewable-energy initiatives in resource-constrained environments. Full article

Provincial innovation systems can be understood as complex adaptive networks in which connectivity and resilience-enabling conditions emerge from heterogeneous local capabilities, spatial constraints, and relational configurations. Taking 95 county-level units in Jiangsu Province, China, as the study area, this study constructs a county-level innovation capability index for 2020–2023 across four dimensions: innovation input, innovation output, innovation environment, and innovation performance. Using this index as the mass variable, a gravity-based potential innovation linkage network is developed, and network analysis indicators are applied to examine its stage-specific structural changes, functional differentiation, and key transmission pathways within the model-derived network. The results show that county-level innovation capability increased across the four observations, while the intra-provincial south–north gradient remained evident. The potential network became increasingly connected, but this increase in connectivity did not lead to structural equalization. Instead, linkages were selectively reinforced around high-capability nodes and spatially proximate areas, indicating local clustering, potentially path-dependent organization, and selective connectivity. County-level units performed differentiated systemic roles as core-organizing, system-supporting, and connector nodes, shaped jointly by innovation capability, spatial location, and network embeddedness. The identified key transmission pathways exhibited a multi-level structural configuration involving intra-cluster reinforcement, intercity corridor continuity along the Yangtze River, and short-chain embedding of peripheral nodes. These findings suggest that provincial innovation systems may exhibit selective structural organization rather than uniform relational development, shaped by capability asymmetry, spatial proximity, and relational configuration. Because the network is derived from innovation capability and geographical distance, the identified linkages and pathways represent model-estimated relational opportunities rather than directly observed knowledge, technology, or innovation flows. Within this interpretive boundary, county-level nodes and key transmission pathways provide insights into system connectivity and resilience-oriented governance. Full article

The recent global energy crisis and the instability of the oil market have prompted scientists to explore innovative ways to produce alternative energy sources such as biodiesel. Current chemical processes for converting waste into biodiesel use catalyst-promoted conventional heating, ultrasonication, and magnetron-irradiated electromagnetic microwave irradiation, although developing more efficient, ecologically friendly methods remains challenging. The main goal of this research was to develop a novel, rapid, and efficient method for biodiesel production from waste cooking fats and oils (brown grease), using gyrotron-generated electromagnetic radiation. To achieve this goal, we investigated the effects of gyrotron radiation parameters, the heterogeneous catalyst WS₂, and the ratio of the reacting components on the efficiency of biodiesel production. Brown grease and its components, such as oleic acid, linoleic acid, triolein, and their mixtures, were explored as a source for biodiesel production. We selected promising conditions to develop a technological process for biodiesel production. As a result of our study, novel gyrotron-activated methods for biodiesel production using heterogeneous catalysts have been developed, and the production parameters have been improved. Full article

As digital technologies continue to evolve, intelligent manufacturing technology represented by industrial robots has been increasingly integrated into various stages of enterprise production and operational activities. This trend has created new opportunities for enterprises to advance green transformation and enhance the level of sustainable green innovation. Based on data from Chinese A-share listed firms, this study empirically examines the effect of industrial robot application on sustainable green innovation of enterprises. The study finds that industrial robot application significantly enhances sustainable green innovation of enterprises. The underlying mechanisms mainly operate through the optimization of human capital structure and government-specific subsidies. Meanwhile, industrial robot application exhibits significant peer spillover effect, which can generate demonstration and pressure transmission effects among enterprises within the same industry and region, thereby promoting the coordinated improvement of sustainable green innovation. Heterogeneity analysis further reveals that the promoting effect of industrial robot application on sustainable green innovation is more pronounced in non-state-owned enterprises, labor-intensive enterprises, enterprises whose executives have an environmental background, and enterprises in regions with stricter environmental regulation. Furthermore, the establishment of regional environmental courts can strengthen the positive effect of industrial robot application on sustainable green innovation of enterprises. The results of the extended analysis further demonstrate that the contribution of industrial robot application to sustainable green innovation mainly stems from its ‘’leverage effect’’ on overall corporate innovation activities, rather than from the ‘’crowding-out effect’’ caused by compressing other technological innovation activities. This study not only enriches the literature on the environmental effects of industrial robot application but also provides new insights into how enterprises can leverage intelligent technologies such as industrial robots to achieve green transformation. Full article

Urban–rural integration, as a pivotal strategy for reshaping the relationship between cities and the countryside and promoting balanced regional development in the current era, carries considerable weight for the green transition of agricultural systems. This study utilizes panel data from 31 Chinese provincial units over the 2011–2023 period to construct a four-dimensional (economic, social, spatial, and ecological) assessment framework for urban–rural integration. It then applies the SBM-GML model to estimate agricultural green total factor productivity and systematically investigates the impact and underlying mechanisms of integration on that productivity. The principal findings are as follows: (1) Urban–rural integration significantly boosts agricultural green total factor productivity, and this outcome remains robust after a variety of sensitivity checks and corrections for potential endogeneity. (2) Mechanism tests further reveal that the primary conduits through which such integration raises AGTFP are the upgrading of human capital and the proliferation of agricultural socialized services. (3) Analysis of moderating effects indicates that both innovation in agricultural science and technology and government fiscal support for farming positively reinforce the facilitative impact of urban–rural integration on agricultural green total factor productivity. (4) Results from heterogeneity analysis suggest that the green productivity effect of such integration is strongest in major grain-producing areas, weaker in major grain-selling areas, and not statistically detectable in grain production–marketing balance regions. Full article

Green technological innovation is widely recognized as a critical driver of sustainable development. This study examines the impact of green taxation on green technological innovation using panel data from 30 Chinese provinces from 2007 to 2022. It distinguishes between narrow and broad green taxation. Using baseline regression, spatial Durbin, and threshold models, the analysis reveals that the green tax reform significantly promotes green technological innovation. Broad green taxation has a stronger effect than narrow green taxation. Narrow green taxation shows significant spatial spillover effects. The impact of both narrow and broad green taxes on green technological innovation shows spatial heterogeneity, with the strongest main effect in the eastern regions. The threshold analysis further shows that surpassing the industrialization threshold significantly enhances green technological innovation, regardless of whether narrow or broad green taxes are used. These empirical results indicate that a differentiated green taxation can promote green technological innovation and achieve sustainable development goals. This study provides policy insights for optimizing green fiscal tools to promote innovation-driven sustainable development. Full article

Artificial intelligence (AI) is widely viewed as a technological foundation for organizational resilience. Yet firms may strategically exaggerate their AI-related narratives without corresponding substantive investment. This study examines whether such AI washing is associated with lower organizational resilience. We conceptualize AI washing as a narrative–investment misalignment within organizational systems, in which symbolic AI claims move ahead of substantive AI investment and capability formation. Based on Chinese A-share listed firms during 2010–2024, we develop a firm-level AI washing index by comparing firms’ within-industry ranking in AI disclosure with their within-industry ranking in actual AI investment. AI disclosure is identified from annual reports using a large language model, while actual AI investment is measured through AI-related software and hardware investments. Using double-debiased machine learning, we estimate a significantly negative association between AI washing and organizational resilience. Economically, a one-standard-deviation increase in AI washing is associated with a decline in organizational resilience equivalent to approximately 3.276% of the average annual change in organizational resilience. This estimated pattern remains stable when we employ alternative variable constructions, replace the machine learning algorithms, adjust the cross-fitting folds, use propensity score matching, and further apply a deep instrumental variable strategy. Mechanism tests based on organizational legitimacy provide evidence consistent with legitimacy-related transmission channels, suggesting that AI washing is associated with lower resilience through weakened pragmatic, moral, and cognitive legitimacy under the maintained mediation assumptions. Further analysis reveals an asymmetric pattern: firms whose AI narratives exceed actual investment experience lower resilience, whereas firms whose actual investment exceeds external narratives exhibit higher resilience. The negative estimated association is particularly evident in high-tech industries, enterprises with established bank-firm ties, and enterprises with higher educational heterogeneity in their top management teams. This study advances research on AI disclosure and organizational resilience by showing that symbolic AI narratives can signal system-level fragility when technological claims are misaligned with substantive capability formation. Full article

Universal access to sanitation in environmentally constrained and territorially heterogeneous settings demands decision frameworks capable of transcending cost-dominant planning approaches. This study develops a multi-criteria decision framework based on the Analytic Hierarchy Process (AHP) to support sustainable sewer technology selection. The model integrates technical, economic, and socio-environmental criteria within a hierarchical structure, incorporating structured expert judgment with consistency verification. The framework is applied to a real case study in Ciudad del Plata, Uruguay, an environmentally sensitive area with medium–low urban density. Results indicate that when socio-environmental criteria are explicitly prioritized, the Condominial system achieves the highest global score (35.9%), outperforming both the Conventional and Small-Diameter alternatives. Sensitivity analysis confirms the stability of the ranking under moderate variations in criteria weights. Beyond the specific case evaluated, the proposed framework advances sustainable infrastructure governance by providing a transparent, transferable, and replicable decision-support tool for sanitation planning under complex territorial conditions. Full article

Background: Personalized nutrition, also referred to as precision nutrition, is an emerging approach that integrates genetic, metabolic, phenotypic, behavioral, and environmental characteristics to develop individualized dietary strategies. Obesity, metabolic syndrome (MetS), and metabolic dysfunction-associated steatotic liver disease (MASLD) represent interconnected disorders with substantial inter-individual variability in disease development, metabolic risk, and response to dietary interventions. Although body mass index (BMI) remains widely used for obesity classification, it does not adequately capture differences in body composition, fat distribution, or metabolic health. Consequently, individuals with normal-weight obesity (NWO), characterized by excessive body fat accumulation despite a normal BMI, may remain unidentified despite increased cardiometabolic risk.This narrative review critically evaluates the current evidence on the potential role of personalized nutrition in the prevention and management of obesity, MetS, MASLD, and related cardiometabolic abnormalities. Particular attention is given to five major domains: nutrigenetics, gut microbiota, metabolic phenotyping, body composition assessment, and digital health technologies, with emphasis on their current clinical applicability and limitations. Methods: A structured narrative review was performed using PubMed, Scopus, and Web of Science to identify English-language studies (2003–2026) on personalized nutrition in obesity, normal-weight obesity, metabolic syndrome, and MASLD. Eligible studies were selected according to predefined inclusion and exclusion criteria, and 31 publications were included in the qualitative synthesis. Results: Current evidence suggests that personalized nutrition strategies may contribute to improvements in body weight regulation, insulin sensitivity, lipid metabolism, and liver-related outcomes; however, the magnitude and consistency of these effects remain variable. The integration of genetic, metabolic, microbiome, and phenotypic information may improve individual risk stratification and help identify high-risk groups, including individuals with NWO who may not be recognized through BMI-based assessment alone. Emerging approaches involving multi-omics technologies, microbiome profiling, wearable devices, continuous glucose monitoring, and artificial intelligence-based tools provide promising opportunities for individualized dietary interventions. Nevertheless, limitations related to methodological heterogeneity, insufficient standardization, limited external validation, and the scarcity of long-term pragmatic clinical trials currently restrict their routine implementation. Conclusions: Personalized nutrition represents a promising but still evolving approach for addressing obesity and its metabolic complications, including MetS and MASLD. While the integration of biological, phenotypic, and digital information may support more targeted dietary recommendations, current evidence does not yet fully establish the clinical effectiveness and cost-effectiveness of these approaches in routine care. Future large-scale, longitudinal, and well-designed randomized controlled trials are required to determine which personalized nutrition strategies provide clinically meaningful benefits and for which patient populations. Full article

Amid rising global economic uncertainty and frequent external shocks, strengthening marine economic resilience has become a core priority for coastal nations to stabilize industrial supply chains and achieve sustainable marine development. China’s traditional resource-driven marine economy faces persistent structural bottlenecks, including homogeneous industrial structure, low value addition and weak risk resistance. As a landmark national policy for sustainable marine economic growth, the Marine Economic Innovation and Development Policy (MEIDP) has been piloted in 15 coastal cities across two batches, yet its causal impact on marine economic resilience remains under systematic evaluation. Using panel data of 51 Chinese coastal cities from 2008 to 2023, this study employs a multi-period difference-in-differences approach with supporting analyses to systematically evaluate the MEIDP’s impact on marine economic resilience, as well as its moderating mechanisms and heterogeneous patterns. The key findings are threefold. First, the MEIDP significantly improves coastal cities’ marine economic resilience, and this positive effect remains stable after multiple robustness tests. Second, public health emergencies exert a significant positive moderating effect, where the industrial support capacity and risk-resilience foundations established through policy implementation function more effectively under shock conditions, thereby amplifying the enhancement of resilience. Third, the policy effect shows prominent heterogeneity, being more pronounced in high-tourism cities and the Northern Marine Economic Circle, while statistically insignificant in low-tourism cities and the Southern Marine Economic Circle. This study enriches the theoretical framework of marine economic policy evaluation and provides empirical evidence from a major developing country for global marine governance, confirming that marine policies that promote innovation are an effective path to strengthen economic risk resistance. In light of these findings, we propose targeted policy recommendations to steadily enhance overall marine economic resilience. Coastal regions should deepen marine policies that promote innovation to bolster industrial upgrading and technological empowerment, adopt differentiated schemes aligned with local industrial foundations and resource endowments, promote marine industrial diversification and chain extension to reduce structural vulnerability, and improve public risk response mechanisms to strengthen the counter-cyclical buffering capacity of the marine economy. Full article

Online shopping is expanding rapidly in emerging European markets, yet many consumers still combine digital channels with offline verification. This study asks whether the resulting heterogeneity among young consumers is genuinely complex or reducible to a simpler structure. Drawing on technology-acceptance and perceived-risk perspectives, it analyses survey data from 457 Romanian university students, of whom 269 were routed to eight attitudinal items on online smartphone purchasing. The questionnaire was distributed to students at two Romanian universities through institutional email and faculty social media accounts, yielding a non-probability convenience sample; no probability-based selection procedure was applied. After examining the dimensionality and reliability of the items through exploratory factor analysis, K-means clustering was used to segment respondents, and the solution was checked against hierarchical clustering. Two segments emerged: cautious, lower-online-orientation consumers, who report lower perceived convenience, speed, price advantage, and overall use of online purchasing, and online-oriented adopters, who view digital channels as efficient and convenient. Rather than many fine-grained segments, the data point to a dominant behavioural axis, namely overall orientation towards online purchasing. The findings provide evidence consistent with a parsimonious two-segment account of consumer heterogeneity in a rapidly developing digital market, and they suggest differentiated omnichannel strategies: confidence-building and risk-reduction measures for cautious consumers and experience optimisation for digital adopters. Full article

This study examines the relationship between corporate financial technology (FinTech) disclosure and environmental, social, and governance (ESG) reporting performance among non-financial firms listed on the Saudi Stock Exchange (Tadawul), with a focus on the post-COVID period from 2021 to 2024. Using an ESG Disclosure Index (ESGDI) constructed from annual reports and a textual measure of FinTech adoption, the analysis provides market-level evidence on the evolution of digital transformation and ESG disclosure in Saudi Arabia. Descriptive results indicate that ESG reporting among Tadawul firms is moderate yet heterogeneous, with governance disclosure consistently stronger than environmental and social components. Correlation analysis indicates a positive association between FinTech disclosure and overall ESG disclosure, particularly within the environmental pillar. Regression results further show that the firms with stronger FinTech disclosure tend to report higher ESGDI scores. The two-way fixed effects (TWFE) model yields statistically significant results, and the direction of the relationship remains consistent with theoretical expectations. Pillar-level analysis suggests that digital transformation is most closely aligned with environmental reporting. Taken together, the results indicate that sustainability disclosure and digital capabilities appear to co-develop in the Tadawul market. Businesses may improve their ability to track, organize, and disseminate ESG-related data by investing in digital reporting systems, analytics, and technology modernization. In this way, FinTech serves as a governance-supporting instrument that improves transparency and reporting discipline in addition to being a financial innovation. This study adds to the expanding body of knowledge by providing important emerging-market-level evidence from the Saudi capital market and highlighting how FinTech can support sustainability-driven growth in an institutional context undergoing rapid transformation. Full article

Warm mix asphalt (WMA) provides a sustainable way of lowering production temperatures, reducing energy use for sustainable pavement construction; however, moisture damage affects its durability. Reclaimed asphalt pavement (RAP) contains aged binder that is stiffer, harder, and more brittle than virgin binder, resulting in asphalt mixtures with higher stiffness/modulus. This review examines the effect of incorporating RAP to amend the moisture damage susceptibility of WMA. It surveys the various moisture-damage failures reported in the literature on WMA with RAP mixes, including adhesive and cohesive failures, as well as hydraulic scouring and aggregate fracture. The analysis further explains the influence of WMA technology, RAP content, rejuvenation, and interfacial chemistry on the moisture durability of WMA-RAP mixtures. The strengths and limitations of the conventional and emerging moisture damage evaluation tests, including AASHTO T 283 tensile strength ratio (TSR), boiling water test (BWT), surface free energy (SFE), and fracture-energy-based approaches, were compared. This mechanistic synthesis linking production-related moisture sources, RAP heterogeneity and practical mitigation strategies highlights why reliance on TSR alone can conceal moisture-cracking vulnerability. The synthesis clarifies how RAP changes the moisture damage susceptibility of WMA to retain the environmental, economic and social benefits and circularity without compromising durability. This review proposes a practical roadmap based on technology-specific screening, multi-metric performance evaluation, and construction quality control for more reliable WMA-RAP specifications. Full article