Near real-time and next-day prediction for Escherichia coli (E. coli) concentrations in highly urbanized watersheds.

Abstract The cultural ecosystem services (CES) framework allows to systematically analyse non‐material human–nature relationships and can help to increase the recognition and scope of various intangible place‐based values. Although the amount of scientific literature addressing CES has increased over the last few decades, studies largely focus only on a limited portfolio of ‘prominent’ CES categories. The objective of this study was to explore a broad range of CES that people use in various landscapes. Reflecting the call to broaden conceptualisations of CES, we aimed to explore which CES contribute to place‐based emotions and eudaimonic values as well. We applied a combination of sociocultural valuation methods, including focus group discussions and intercept questionnaire surveys, in two protected landscape areas in the Czech Republic. The survey included various free‐listing exercises capturing CES in qualitative terms and a preference assessment using indicator statements. To identify a broad range of CES, we employed a combination of deductive and inductive approaches to CES classification. Visitors to the case study areas use and value a wide range of CES: free‐listing exercises identified 13–15 categories of them. In the context of reasons why people go to nature or visit their favourite places, Recreation, Ecophilia and Aesthetics were the CES most often mentioned. Our results also uncovered that many CES contribute to place‐based emotions and eudaimonic values, with CES Mental and physical health being the most prominent category. The exploratory nature of the research and the inclusive approach to CES classification facilitated the emergence of uncommon categories such as Ecophilia, which appeared among the most frequently mentioned CES. Our results confirm that using plural methods and within‐methods pluralizing approaches such as different question framings can enrich the CES diversity to be captured. We suggest that providing evidence about the use of CES can support better‐informed environmental management and landscape planning that seeks to balance the CES‐related multifunctionality of landscapes in protected areas, aligning conservation and landscape management more closely with the actual use and appreciation of CES. Read the free Plain Language Summary for this article on the Journal blog.

This review aims to identify critical environmental degradation issues affecting public health in Assam. A systematic literature search was conducted using Scopus and Google Scholar with the keywords “Environmental Degradation” AND “Public Health” AND “Assam.” Relevant studies were analysed using a qualitative deductive coding approach, guided by a custom-developed codebook based on the study’s objectives. The review reveals widespread contamination of drinking water, soil, and air across Assam, involving pollutants such as arsenic, fluoride, iron, manganese, lead, cadmium, organochlorine pesticides, particulate matter, and microbial agents. These exposures are linked to both acute infections and chronic noncommunicable diseases, disproportionately affecting children, women, and vulnerable communities, including rural and tribal populations. The findings provide a consolidated overview of the environmental health landscape in Assam and highlight significant gaps in the literature. This review offers a foundation for future research and policy interventions aimed at mitigating environmental health risks in the region.

Unravelling the complexity of cancer premetastatic niche - Mechanistic insights and clinical therapies.

Urbanization is a dynamic process that has transformed cities worldwide, shaping social, economic, and environmental landscapes. This current study explores the causes (Economic activities, rural push factors and access to services) and consequences (Environment impacts) of urbanization in Jeddah City, Saudi Arabia. Economic opportunities, rural push factors, and access to essential services are examined as primary causes that attract populations to the city, while environmental degradation, including pollution, loss of green spaces, and increased pressure on resources, is assessed as a major consequence of rapid urban growth. Using a mixed-methods approach combining surveys, interviews, and secondary data analysis, the study provides both quantitative and qualitative insights into the factors influencing urban expansion and its outcomes. The findings reveal that while urbanization offers significant economic and social benefits, it also poses critical environmental challenges, highlighting the need for sustainable urban planning strategies. This research contributes to the broader understanding of urban growth in rapidly developing regions and provides evidence-based recommendations for policymakers and urban planners in Jeddah and similar cities.

In contemporary urban environments, landscaping has emerged as a core component that extends beyond aesthetic enhancement, contributing significantly to the improvement of residential quality, the physical and psychological well-being of residents, and the strengthening of local identity and urban competitiveness. Urban landscape resources—such as parks, green spaces, and view corridors—are closely associated with residential satisfaction and play a critical role in shaping real estate values. As demand for pleasant living conditions and environmental welfare increases in densely populated cities, the need for systematic research on the relationship between landscaping and real estate value has grown substantially. This study aims to empirically analyze the impact of urban landscaping factors on real estate values and to identify the key elements influencing value formation. To achieve this, the Analytic Hierarchy Process (AHP) was applied to evaluate the relative importance of landscaping attributes, based on survey responses from apartment residents, real estate practitioners, and landscape experts. During the analysis, landscaping factors were structured into a hierarchical framework consisting of upper- and lower-level categories, after which a targeted survey was conducted. Consistency verification was performed to ensure reliable weighting results. The findings reveal that green coverage within residential complexes and accessibility to parks—representing the overall quality of landscaping—are the most influential determinants of real estate value. These results confirm that landscaping contributes not only to visual satisfaction but also to substantial economic value creation, underscoring the importance of strategic planning and management of landscape environments. The study suggests the necessity of strengthening institutional requirements for minimum green coverage ratios in urban planning and emphasizes the need to consider park accessibility as a key locational factor in residential development.

Linking green space patterns to elderly stress: The serial roles of greenery perception and physical activity.

The article is devoted to analyzing the dynamics of spatio-temporal changes in water bodies within the Semipalatinsk Test Site using remote sensing data based on the Google Earth Engine platform, with the aim of developing a map of surface water and irrigation systems to support landscape planning of the area. Landsat and Sentinel-2 satellite imagery, ERA5-Land climatic data, and the SRTM digital elevation model were used as the primary input datasets. Water surfaces were extracted using the Modified Normalized Difference Water Index (MNDWI) method. The results revealed that the largest extents of water surfaces were observed in years characterized by cold and snowy winters (2000 and 2010), whereas the smallest extents occurred during warm and low-snow periods (1996, 2012, and 2024). The proportion of temporary water bodies exceeds 60%, reflecting the instability of the hydrological regime and its strong dependence on climatic variability. The use of modern platforms such as Google Earth Engine for identifying spatio-temporal changes in water bodies has proven to be effective and demonstrates great potential for water resource management and dynamic assessment. The obtained results can be applied for environmental monitoring and landscape planning in the development of the former test site areas for agricultural purposes.

The global redistribution of species through human agency is one of the defining ecological signatures of the Anthropocene, with biological invasions reshaping biodiversity patterns, ecosystem processes and services, and species interactions globally. Here, we review the facets underlying the spread of non-native species - the key process by which introductions translate into large-scale invasions. In particular, we synthesise the ecological, evolutionary, and anthropogenic mechanisms underpinning the spread of non-native species, highlighting how dispersal, recruitment, and establishment interact across spatial and temporal scales. We examine the dynamics of non-native species spread in animals, plants, fungi, and pathogens, as well as across terrestrial, freshwater, and marine realms, with particular attention to the dynamics and processes modulating spread. We further evaluate essential phenomena of non-native species spread, such as the role of invasion fronts, Allee effects, propagule pressure, interactions with environmental change, landscape properties, and biotic interactions. We then outline how spread can be measured, modelled, and predicted using tools ranging from classical diffusion models to cutting-edge Artificial Intelligence and individual-based simulations. By offering a cross-system and cross-scale synthesis, this review advances the theoretical and practical understanding of non-native species spread for supporting policy and management.

Purpose This study is empirically conducted with an emphasis on exploring key factor constructs for an implementation of world class manufacturing system (WCMS) by Make-in-India manufacturers in the Indian manufacturing context. This study also intends to measure the significant influence of WCMS implementation on competitive advantage in the manufacturing operations. Design/methodology/approach This empirical study uses structured research instruments administered among 132 production managers/plant supervisors/quality managers. The target respondents were sampled using judgmental sampling method that they had experience in implementing any one of the WCM practices, principles, techniques and tools for a period of more than one year. Findings In this study, exploratory factor analysis was used to identify 29 key factor constructs in the context of WCMS implementation and were classified into three latent constructs such as “WCM practices,” “Business priorities” and “Lean initiatives.” These key factor constructs were validated through a sample of 132 Make-in-India manufacturers being surveyed in India. Practical implications In the landscape of competitive business environment, the manufactures in general and Make-in-India manufactures in particular need to acknowledge that the intent of being world class is not just a matter of producing quality products, the ability to integrate WCM practices, principles and techniques in the manufacturing operations to become competitive in the global market. Originality/value Although, a few studies have witnessed a phenomenal growth in the implementation of WCMS, the underlying factors that drive Make-in-India manufacturers were not addressed in the context of developing countries like India. To the best of the authors’ knowledge, this study is first of its kind to bridge this research gap and identify the key factor constructs driving the implementation of WCMS by Make-in-India manufacturers in the journey of achieving competitive advantage in their manufacturing operations.

In an increasingly volatile geopolitical and environmental landscape, global supply chains are under constant threat from a myriad of disruptions, ranging from political conflicts and trade restrictions to natural disasters and port congestion. This paper investigates the integration of predictive Artificial Intelligence (AI) models into international logistics systems as a proactive mechanism to anticipate, evaluate, and mitigate such disruptions. Utilizing a multidisciplinary approach, this study synthesizes advancements in machine learning, network optimization, and real‑time data analytics to demonstrate how AI is revolutionizing supply chain risk management. Through comparative analysis and empirical examples, it is shown that predictive AI not only enhances operational resilience but also offers economic advantages by minimizing downtime and rerouting logistics in near‑real‑time. The paper presents a framework for implementing AI‑driven predictive systems within global logistics operations, emphasizing ethical considerations, data governance, and international policy harmonization. Ultimately, this research highlights AI’s transformative potential in shaping a more adaptive, secure, and efficient global trade network.

This study investigates the influence of environmental comfort and landscape visibility on node extraction and tour route optimization by integrating spatial data analysis with site design. Three algorithmic models—environmental comfort analysis, dynamic tour route analysis, and multidimensional plot value evaluation—were developed using Grasshopper (GH) combined with Python 3.12.0. These models comprehensively quantified the solar radiation and wind conditions in Dazhai Village, Chengbu County, simulated visitor perspectives to calculate landscape visibility, and derived a quantitative visual perception index. Analysis of 197 sampling points revealed superior environmental comfort and scenic views at the village’s peripheries and open areas. Based on annual comfort duration percentages and dynamic tour evaluation coefficients, 13 activity nodes with comfort duration rates exceeding 25.68% were identified, enabling the extraction of scientifically optimized tour routes. The planning scope was further refined by integrating the village’s visual perception index to account for multi-factor influences. Establishing a digital model for traditional village activity node extraction, tour route optimization, and plot value evaluation effectively enhances spatial analysis’s efficiency and scientific rigor. This approach enriches the design methodology system for environmental comfort and landscape visibility in traditional villages while offering new perspectives for their conservation research.

The role of commensal anaerobic bacteria in chronic respiratory infections is unclear, yet they can exist in abundances comparable to canonical pathogens in vivo. Their contributions to the metabolic landscape of the host environment may influence pathogen behavior by competing for nutrients and creating inhospitable conditions via toxic metabolites. Here, we show that the anaerobe-derived short-chain fatty acids (SCFAs) propionate and butyrate negatively affect Staphylococcus aureus physiology by disrupting branched-chain fatty acid (BCFA) metabolism. In turn, alterations to BCFA abundance impair S. aureus growth, compromise membrane integrity, diminish expression of the accessory gene regulator quorum-sensing system, and increase sensitivity to membrane-targeting antimicrobials. Disrupted BCFA metabolism also reduced S. aureus fitness in competition with Pseudomonas aeruginosa, suggesting that airway microbiome composition and the metabolites they exchange can directly impact pathogen succession over time. The pleiotropic effects of SCFAs on S. aureus fitness and their ubiquity as metabolites in the human host also suggest that they may be effective as adjuvants to traditional antimicrobial agents when used in combination.IMPORTANCEStaphylococcus aureus is a primary pathogen of chronic airway disease yet is also found in the upper airways of 30%-50% of the population to no obvious detriment. Thus, identifying the host and/or microbial factors that tip the balance between its commensal and pathogenic states may be key to its control. Here, we reveal that short-chain fatty acids produced by commensal microbiota promote a marked remodeling of the S. aureus lipid membrane that, in turn, sensitizes the pathogen to antimicrobials, disrupts accessory gene regulator quorum signaling, and reduces its competitive fitness. Altogether, these data suggest that co-colonizing microbiota and the metabolites they exchange with S. aureus may be key players in the microbial ecology of airway disease.

In view of the problems of low efficiency and poor real-time performance in the monitoring and management of the landscape environment of water ecological wetlands, this paper designs an intelligent analysis and information intelligent control system for online monitoring of the landscape environment of water ecological wetlands. Through advanced sensor networks and data acquisition technologies, the system monitors key indicators such as water temperature, pH value, dissolved oxygen, and turbidity in the wetland landscape environment in real time, and combines machine learning and intelligent data analysis algorithms to achieve efficient data processing and accurate analysis. The experimental results show that the system performs well in the detection of indicators such as water temperature, pH value, dissolved oxygen, and turbidity at the monitoring point. The P-value of the predicted value and the actual value are both greater than 0.05, and the error range is within a controllable range, with high detection accuracy. At the same time, the response time and data processing time of the system are controlled within 1.5 seconds, the early warning accuracy rate reaches 100%, and the water quality equipment can be effectively regulated to ensure the health of the water ecological environment. Studies have shown that the system has significant advantages in monitoring accuracy, real-time performance, early warning capability, and intelligent control, provides important technical support for the protection and management of aquatic ecological wetland landscape environment, and has broad application prospects.

This study investigates how anthropogenic impacts, local environmental variables, spatial conditions, and landscape characteristics influence fish assemblage structure in streams of the Eastern Amazon. The fieldwork was conducted in 30 streams within the Atlantic Coast/Northeast Pará hydrographic region during October 2023. Fish were sampled using circular hand nets, with six hours of effort per stream. Environmental data encompassed habitat structure, limnological parameters, spatial variables, and landscape features. A total of 7,449 individuals representing 49 species were recorded; species richness ranged from 1 to 20, and Local Contribution to Beta Diversity (LCBD) from 0.0145 to 0.0802. Richness increased with greater leaf litter cover and decreased with higher conductivity. Regarding spatial factors, richness showed a positive association with the third axis of Asymmetric Eigenvector Maps (AEM3). LCBD values increased with higher conductivity, pH, and wood debris, but decreased with greater surrounding pasture cover. Redundancy analysis (RDA) indicated that species composition could be primarily explained by local habitat characteristics such as substrate size, leaf litter, and shelter availability, as well as spatial structure represented by AEM3. Specific species were associated with distinct habitat conditions. These findings underscore the strong influence of habitat structure, physicochemical properties, and spatial dynamics on fish assemblages, highlighting their sensitivity to anthropogenic disturbances and the importance of conserving riparian environments in Amazonian stream ecosystems.

Tectonic shifts in the global geo-political, public health, environmental, technological and institutional landscapes in the last decade have compelled the critical re-examination of our inherited ways of teaching, learning and doing mental health science. As mental health gains recognition as a global development and investment priority, education and training must evolve to meet the complex, ever-changing and context-sensitive demands of the field. Global mental health, a disruptive, interdisciplinary field of science and practice committed to redressing regional and in-country disparities in mental healthcare financing, access and outcomes, has a particularly strong mandate to rethink how professionals are prepared to act ethically, competently and adaptively. This editorial advocates for a shift towards competency-based, experiential and interdisciplinary learning frameworks that align with the field’s transformative ambit. Specifically, it puts forward promising pedagogical tools and other innovations, with the hope that they will become routine practice. It concludes with a call for papers exploring cutting-edge approaches to teaching, training and skills development in global mental health and allied disciplines.

Climate change is profoundly reshaping watershed hydrological regimes and threatening the sustainability of regional ecosystems, rendering traditional ecological restoration planning—primarily reliant on static baselines—insufficient to support long-term resilience under future environmental conditions. To enhance the sustainability of metropolitan ecological restoration, this study develops a climate-adaptive restoration framework for the Wuhan Metropolitan Area, structured around “climate scenario—hydrological simulation—zoning delineation—strategy formulation.” The framework aims to elucidate how projected hydrological shifts constrain the spatial configuration of ecological restoration. Under the RCP4.5 (Representative Concentration Pathway 4.5) scenario, the WEP-L (Water and Energy transfer Processes in Large river basins) distributed hydrological model was calibrated and validated using observed hydrological data from 2016–2020 and subsequently applied to simulate the spatiotemporal evolution of precipitation, evapotranspiration, runoff, and total water resources in 2035. Hydrological trend analyses were further conducted at the secondary watershed scale to assess the differentiated impacts of future hydrological changes across planning units. Based on these simulations, ecological sensitivity and ecosystem service assessments were integrated to identify priority restoration areas, forming a “five-zone × three-tier” sustainable restoration zoning system encompassing farmland restoration, forest ecological restoration, soil and water conservation restoration, river and lake wetland ecological restoration, and urban habitat improvement restoration, classified into general, important, and extremely important levels. A comprehensive “four-water” management scheme—addressing water security, water resources, water environment, and water landscape—was subsequently proposed to strengthen the sustainable supply capacity and overall resilience of metropolitan ecosystems. Results indicate that by 2035, hydrological processes in the Wuhan Metropolitan Area will exhibit pronounced spatial heterogeneity, with uneven changes in precipitation and runoff further intensifying disparities in regional water availability. These findings highlight the necessity of incorporating scenario-based hydrological constraints into sustainable ecological restoration planning. The proposed technical framework provides a transferable pathway for enhancing watershed ecosystem sustainability and resilience under climate change.

IntroductionSolanum nigrum, a member of the Solanaceae family, holds significant importance in various aspects, including edible and medicinal uses, ecological management, and environmental landscaping. The leaf edges of S. nigrum exhibit 4–5 significant serrations, and the splitting of these leaf margins plays a crucial role in the plant’s adaptation to environmental shifts.MethodsIn this study, we systematically analyzed the molecular mechanism of leaf margin fission in S. nigrum by combining RNA sequencing, weighted gene co-expression network analysis, and overexpression transgenic technology using leaves from five growth stages of S. nigrum during the flowering period as materials.ResultsTranscriptome analysis revealed that 30,311 differentially expressed genes were activated from leaf bud to mature leaf, and these genes were significantly enriched in metabolic pathways related to signal transduction and glycosynthesis. Differential genes were hierarchically clustered into 13 modules. The correlations of these modules with different growth stages of S. nigrum leaves, as well as the number and depth of leaf notches were analyzed. It was found that the turquoise expression module (ME1) was significantly and positively correlated with the leaf bud stage (r = 0.94, p < 0.01), while negatively correlated with the number and depth of leaf notches. Three highly connected hub genes were identified from network interactions analysis of genes related to the leaf differentiation pathway in Module 1. From the intersection of the turquoise module and the 2 clusters screened by temporal analysis, the core gene (SnNAC90) for leaf margin fission in lobelia was identified. The regulatory role of the SnNAC90 gene in tobacco leaves was preliminarily verified by transgenic technology.DiscussionIt was hypothesized that it might positively regulate leaf margin fission in S. nigrum. Preliminary speculation on its regulatory role in S. nigrum leaves. This study, for the first time, revealed the regulatory mechanism of leaf margin division in S. nigrum, providing a theoretical basis for enriching its germplasm resources and serving as a reference basis for cultivating leaf plants.

Quantitative real-time PCR (q-RT-PCR) is a widely used method for measuring gene expression, but its accuracy depends on the use of stable reference genes for data normalization. In this study, we evaluated the expression stability of seven candidate reference genes (RPS18, RPS5, RPL32, RPL8, EF-1α, β-Actin, and GAPDH) in the small carpenter bee Ceratina calcarata across developmental stages (larvae, pupae, adults) and different landscape environments (conventional farms, organic farms, and roadside sites). Using four analytical algorithms, GeNorm, NormFinder, BestKeeper, and the comparative ΔCt method, we identified RPS18 and RPL8 as the most stable reference genes under varying biological and environmental conditions. These findings were further supported by RefFinder, which integrates results from all algorithms. Our study provides the first validated reference genes for C. calcarata, enabling more accurate and reproducible gene expression analysis in this ecologically important wild bee species. This work will support future research in pollinator biology, environmental stress responses, and conservation genomics.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-23816-z.

The widespread production and application of per- and polyfluoroalkyl substances (PFASs) have created a global environmental and public health crisis. This review aimed to consolidate the foundational knowledge on PFASs by synthesizing research on their environmental fate, human health impact, analytical methods, and regulatory status and by highlighting their critical challenges. A comprehensive literature search focusing on publications from the last five years (2020–2025) was conducted using global scientific databases (e.g., PubMed, Web of Science) and regulatory reports (e.g., EPA, ECHA). The persistent and pervasive nature of PFASs stems from the highly stable carbon–fluorine (C-F) bond, leading to their widespread release from diverse industrial and consumer products into water, soil, and air. Key outcomes reveal significant analytical challenges in their detection, including sample matrix complexity, widespread laboratory contamination, and a lack of standards for the vast number of specific compounds. Critical research gaps were identified, particularly the limited data on PFAS concentrations in air and dust, the need for standardized analytical methods and reporting units, and the urgent necessity for developing scalable, sustainable remediation strategies. The ongoing environmental contamination and associated health risks necessitate continued, focused interdisciplinary research to improve detection, risk assessment, and the effective management of this complex class of pollutants.