Search Results (1,077)

Burkholderia is a metabolically versatile genus of Gram-negative bacteria that inhabits niches ranging from soil and water to plants and clinical environments. This review provides an integrated examination of Burkholderia species, focusing on their dual roles as both pathogens and beneficial microorganisms. Key pathogenic species, such as members of the Burkholderia cepacia complex and the Burkholderia pseudomallei group, pose significant threats to human, animal, and plant health due to their intrinsic antibiotic resistance and diverse virulence factors. Conversely, several environmental and plant-associated Burkholderia species promote plant growth, enhance nutrient uptake, and serve as biocontrol agents, supporting sustainable agriculture. We synthesize current knowledge across taxonomy, genomics, pathogenicity, beneficial interactions, and secondary metabolite biosynthesis—including the prolific production of antibiotics, toxins, and volatile organic compounds with pharmaceutical and agricultural potential. Advances in high-throughput genomics are revealing substantial genetic diversity, genome plasticity, and mechanisms underlying both pathogenicity and beneficial traits. Clarifying this dual nature and identifying strategies to mitigate risks will guide the safe and effective exploitation of Burkholderia in medicine, agriculture, and biotechnology. Full article

In the context of rapid urbanization, the connection between humans and nature has progressively diminished. As an essential approach to fostering public ecological awareness and well-being, nature education requires greater integration into urban green space planning and management. This study examines 14 country parks, urban parks, and forest parks in Beijing, conducting questionnaire surveys in six representative parks and collecting 820 valid responses. Combining image semantic segmentation techniques, the research employs the PSPNet model trained on the ADE20K dataset to automatically extract landscape features of nature education spaces. These features are then integrated with visitor perception evaluations through univariate linear regression models to analyze the impact of spatial variables on visitor perceptions. Results indicate that building coverage, plant species density, interpretation sign density, number of artificial interpretations, and number of nature education activities offerings show significant positive correlations (p < 0.05) with visitor perceptions. In contrast, excessive artificial structures exert a negative influence. The R² values of each model ranged from 0.12 to 0.34, indicating that natural education space features possess explanatory power for visitor perceptions but remain influenced by multiple interacting factors. This study establishes a quantitative evaluation framework linking natural education space landscape features to visitor perceptions, providing a scientific basis for natural education planning and spatial optimization in parks within megacity contexts. Full article

Flexible strain sensors capable of conformal integration with living organisms are essential for advanced wearable electronics, human–machine interaction, and plant health. However, many existing sensors require complex fabrication or rely on non-breathable elastomer substrates that interfere with the physiological microenvironment of skin or plant tissues. Here, we present a low-cost, breathable, and highly stretchable strain sensor constructed from biomedical materials, in which a double-layer medical elastic bandage serves as the porous substrate and an intermediate conductive medical elastic tape impregnated with carbon nanotubes (CNTs) ink acts as the sensing layer. Owing to the hierarchical textile porosity and the deformable CNTs percolation network, the sensor achieves a wide strain range of 100%, a gauge factor of up to 2.72, and excellent nonlinear second-order fitting (R² = 0.997). The bandage substrate provides superior air permeability, allowing long-term attachment without obstructing moisture and gas exchange, which is particularly important for maintaining skin comfort and preventing disturbances to plant epidermal physiology. Demonstrations in human joint-motion monitoring and real-time plant growth detection highlight the device’s versatility and biological compatibility. This work offers a simple, low-cost yet effective alternative to sophisticated strain sensors designed for human monitoring and plant growth monitoring, providing a scalable route toward multifunctional wearable sensing platforms. Full article

Curcumin is a natural bioactive compound with demonstrated anticancer activity. However, its poor aqueous solubility and limited bioavailability constrain its therapeutic utility. This study formulated nanoemulsions using marine (salmon oil) and plant (rapeseed oil) lipids to enhance the solubility and delivery of curcumin. The fatty acid profiles and lipid class distributions of both lipid sources were characterized. The resulting nanoemulsions prepared from salmon and rapeseed oils exhibited mean droplet diameters of approximately 170 nm and 220 nm, respectively, and remained physically stable for 30 days at 25 °C. Notably, curcumin-loaded nanoemulsions displayed smaller droplet sizes than their unloaded counterparts, suggesting strong curcumin–lecithin interactions. In vitro cytotoxicity assays demonstrated that the curcumin-loaded nanoemulsions significantly reduced the proliferation of MCF-7 human breast cancer cells (p < 0.001). Collectively, these findings indicate that lipid-based nanoemulsions represent a promising delivery platform for curcumin in the context of breast cancer therapy. Full article

Socio-ecological systems (SESs) exhibit nonlinear feedback across environmental, social, and economic processes, requiring integrative analytical tools capable of representing such coupled dynamics. This study presents a quantitative framework that integrates a compartmental model of a global human–ecosystem with two complementary optimization approaches (Fisher Information (FI) and Multi-Objective Optimization (MOO)) to evaluate policy strategies for sustainability. The model represents biophysical and socio-economic interactions across 15 compartments, incorporating feedback loops between greenhouse gas (GHG) accumulation, temperature anomalies, and trophic–economic dynamics. Six policy-relevant decision variables were selected (wild plant mortality, sectoral prices (agriculture, livestock, and industry), base wages, and resource productivity) and optimized under temporal (25-year) and magnitude (±10%) constraints to ensure policy realism. FI-based optimization enhances system stability, whereas the MOO framework balances environmental, social, and economic objectives using the Ideal Point Method. Both approaches prevent the systemic collapse observed in the baseline scenario. The FI and MOO strategies reduce terminal global temperature by 11.4% and 15.0%, respectively, relative to the baseline (35 °C → 31.0 °C under FI; 35 °C → 29.7 °C under MOO). Resource-use efficiency, measured through the resource requirement coefficient (λ), improves by 8–10% under MOO (0.6767 → 0.6090) and by 6–7% under FI (0.6668 → 0.6262). These outcomes offer actionable guidance for long-term climate policy at national and international scales. The MOO framework provided the most balanced outcomes, enhancing environmental and social performance while maintaining economic viability. Overall, the integration of optimization and information-theoretic approaches within SES models can support evidence-based public policy design, offering actionable pathways toward resilient, efficient, and equitable sustainability transitions. Full article

Background/Objectives: Diet–microbiota interactions shape ageing; however, their sex-specific dimensions remain poorly defined. Human studies rarely stratify analyses by sex, while most evidence of sex-dependent microbial and metabolic responses comes from preclinical models. This review synthesizes current findings on the sex-specific pathways linking diet, microbiota, and healthy ageing. Methods: A narrative review was conducted by integrating human observational studies, randomized controlled trials, and mechanistic animal research. Evidence was organized into four domains: (1) age-related changes in gut microbial composition; (2) microbiota-derived metabolites; (3) dietary patterns and functional nutrients; and (4) sex-specific endocrine and immunometabolism interactions influenced by the gut microbiota. Results: Ageing is characterized by dysbiosis, loss of short-chain fatty acid (SCFA)-producing taxa, expansion of Proteobacteria, and reduced production of key metabolites including butyrate, indoles, and polyamines. Dietary fiber, polyphenols, omega-3 fatty acids, and plant-based proteins help restore these pathways and mitigate inflammaging. Sex differences persist into later life: women show reduced estrobolome activity and SCFA decline after menopause, whereas men display higher levels of pro-atherogenic metabolites such as trimethylamine N-oxide (TMAO). Nutritional interventions, probiotics, and microbial metabolites exhibit sex-dependent responses in both human and animal studies. Conclusions: Diet–microbiota interactions shape ageing outcomes through sex-specific metabolic, hormonal, and immunological pathways. Incorporating sex as a biological variable is essential for developing personalized, nutrition-based strategies to support healthy ageing. Full article

Tomato brown rugose fruit virus (ToBRFV), a highly stable and mechanically transmissible tobamovirus, poses a significant threat to solanaceous crops worldwide, particularly tomato (Solanum lycopersicum). While its transmission via human activities and contaminated materials is well-documented, the role of common phytophagous insects in its epidemiology remains less understood. Henosepilachna vigintioctopunctata, the Hadda beetle, is a common pest of Solanaceae with a host range that overlaps extensively with that of ToBRFV. This study aimed to quantify the beetle’s capacity to act as a mechanical vector and to assess its potential epidemiological impact. Using reverse transcription quantitative PCR (RT-qPCR), we evaluated beetle-mediated transmission efficiency, the persistence of its virus-carrying capacity, and its ability to vector the virus to various solanaceous hosts. Our results demonstrate that H. vigintioctopunctata efficiently acquires and transmits ToBRFV to tomato and other key hosts, including black nightshade (S. nigrum), pepper (Capsicum annuum), and eggplant (Solanum melongena). The virus was retained and remained transmissible by beetles for up to 48 h post-acquisition, providing a significant window for dispersal. Viral particles were most abundant in the digestive tract, consistent with ingestion of infected tissue, and declined rapidly on external body parts, confirming a non-circulative, mechanical transmission mechanism. Furthermore, feeding wounds created by non-viruliferous beetles increased plant susceptibility to subsequent infection from environmental contamination. We conclude that H. vigintioctopunctata acts as a potential mechanical vector that might amplify ToBRFV spread at local and landscape levels. This highlights a synergistic interaction between a native pest and an invasive pathogen, underscoring the necessity of incorporating beetle management into integrated strategies for controlling ToBRFV. Full article

MicroRNAs (miRNAs) are small single-stranded non-coding RNA molecules that regulate gene expression at the post-transcriptional level. Recent studies have demonstrated that plant miRNAs can survive through dietary intake and act as signaling molecules in intercellular communication, proving a cross-kingdom interaction. The aim of the present study was to use computational approaches to identify interactions between Zea mays (maize) miRNAs and human coding mRNAs potentially involved in different biological processes. We identified 961 unique genes potentially regulated by maize miRNAs. Furthermore, functional enrichment analysis via GO and KEGG was carried out focusing primarily on the pathway related to prostate cancer where 13 genes were potentially regulated by 15 maize miRNAs. Our findings not only provide an important insight into the potential effects that maize-derived miRNAs could have on the human body, but also highlight the importance of considering these molecules for further research and potential therapeutic applications against major diseases such as cancer. Full article

Global climate change is exerting a growing impact on agricultural ecosystems. Accurately assessing the spatiotemporal dynamics of agricultural ecosystem respiration and its response mechanisms to climate has therefore emerged as a critical issue in agricultural carbon cycle research and climate change response. It should be noted that the ‘agro-ecosystem’ referred to in this study covers two major types: one is the farmland agro-ecosystem dominated by crop planting (such as farmland, orchard and other artificial management systems), and the other is the grassland agro-ecosystem dominated by herbaceous plants and managed by humans (such as grazing grassland and mowing grassland). Remote sensing technology provides a new way to break through the limitations of traditional ground observation by virtue of its advantages of large-scale and continuous monitoring. Based on the CiteSpace bibliometric method, this study focused on the key time window of 2021–2025, systematically searched the core collection of Web of Science, and finally included 222 related literature. This period marks the initial stage of the rise and rapid development of this interdisciplinary field, enabling us to capture the formation of its knowledge structure and the evolution of its research paradigm from the source. Through the quantitative analysis of this literature, it aims to reveal the research hotspots, development paths and frontier trends in this field. The results show that China occupies a dominant position in this field (135 articles). The evolution of research shows a three-stage development characterized by “technology-driven-method fusion-system coupling,” which is divided into the initial development period (2021–2022), the rapid growth period (2023–2024) and the deepening development period (2025) (because 2025 has not yet ended, this stage is a preliminary discussion). Keyword clustering analysis identified 13 important research directions, including machine learning (# 0 clustering), permafrost (# 1 clustering) and carbon flux (# 2 clustering). It is found that the deep integration of artificial intelligence and remote sensing data is promoting the transformation of research methods from traditional inversion to intelligent modeling. At the same time, the attention to alpine grassland and other ecosystems also reflects the trend that the research frontier extends to the interaction zone between the agricultural ecosystem and the natural environment. Future research should prioritize three key directions: building multi-scale monitoring networks, developing “grey box” models that integrate mechanisms and data fusion, and evaluating the carbon emission reduction efficiency of agricultural management practices. These efforts will provide a theoretical basis for carbon management and climate adaptation in agricultural ecosystems, as well as scientific and technological support for achieving global agricultural sustainable development goals (specifically, SDG13 on climate action and SDG15 on terrestrial ecosystem conservation). Full article

Cadmium (Cd) accumulation in rice poses a serious threat to global food safety and human health. Foliar application of nano-silica (Si) offers a promising remediation strategy, but its efficacy is often limited by poor droplet retention on hydrophobic leaf surfaces. This study hypothesized that surfactants could overcome this barrier by enhancing the foliar performance of nano-Si. Through field experiments, we evaluated the synergistic effects of five surfactants (Polyvinylpyrrolidone (PVP) powder, Aerosol OT (AOT), Rhamnolipid (RH), Didecyldimethylammonium bromide (DDAB), and Alkyl Polyglycoside (APG)) when combined with nano-silica. The results demonstrated that all surfactants significantly improved wetting and retention, with alkyl polyglycoside (APG) and polyvinylpyrrolidone (PVP) being the most effective. These improvements translated into a remarkable suppression of Cd translocation within rice plants. The PVP–nano-Si combination emerged as the most potent treatment, reducing grain Cd content by 50% and achieving the lowest levels of As and Cr among all treatments. Furthermore, this synergistic effect was linked to a significant increase in grain concentrations of manganese (Mn) and zinc (Zn), which exhibit a competitive relationship with Cd. The findings reveal that surfactant co-application not only optimizes the physical application of nano-Si but also triggers beneficial nutrient–Cd interactions, providing a novel and efficient strategy for mitigating Cd contamination in rice. This study provides critical theoretical support for developing efficient and environmentally friendly foliar barrier technologies and supports safe production of rice in lightly to moderately contaminated paddy fields. Full article

Anthocyanins pigment plant tissues, mitigate biotic and abiotic stresses, and deliver human health benefits; raising their content in mung bean (Vigna radiata) sprouts is a long-standing research target. Transcriptome analysis identified VrNAC25, a NAC transcription factor whose expression closely parallels anthocyanin accumulation; functional validation in mung bean confirmed that VrNAC25 acts as a positive regulator of the pathway. Although VrNAC25 does not bind to the promoters of the key structural genes VrDFR or VrLDOX, it indirectly controls anthocyanin synthesis by interacting with the core R2R3-MYB activator VrMYB90, previously established as the central regulator of anthocyanin production in mung beans. This interaction operates at both transcriptional and protein levels, thereby amplifying the expression of downstream structural genes and boosting pigment accumulation. Our findings refine the molecular network governing anthocyanin biosynthesis in sprouts and provide a clear theoretical basis for breeding or biotechnological strategies aimed at enhancing the nutritional quality and commercial value of mung bean products through light treatment or by selecting an anthocyanin-rich mung bean variety. Full article

Multi-omics data offers rich insights into complex traits across organisms, yet integrating and analyzing these datasets for phenotype prediction and marker discovery remains challenging. Researchers need accessible tools that combine deep learning, hyperparameter optimization, visualization, and downstream analysis in a unified web platform. To address this, we developed G2PDeep-v2, a web-based platform powered by deep learning for phenotype prediction and marker discovery from multi-omics data across a wide range of organisms, including humans and plants. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm on high-performance computing resources. Users can visualize the results of phenotype and markers predictions and perform Gene Set Enrichment Analysis for the significant markers to provide insights into the molecular mechanisms underlying complex diseases, conditions and other biological phenotypes being studied. Full article

This paper presents the design of an autonomous robot guide for a museum-like environment in a motorcycle assembly plant. The system integrates Industry 4.0 technologies such as artificial vision, indoor positioning, generative artificial intelligence, and cloud connectivity to enhance the visitor experience. The development follows the Design Inclusive Research (DIR) methodology and the VDI 2206 standard to ensure a structured scientific and engineering process. A key innovation is the integration of mmWave sensors alongside LiDAR and RGB-D cameras, enabling reliable human detection and improved navigation safety in reflective indoor environments, as well as the deployment of an open-source large language model for natural, on-device interaction with visitors. The current results include the complete mechanical, electronic, and software architecture; simulation validation; and a preliminary implementation in the real museum environment, where the system demonstrated consistent autonomous navigation, stable performance, and effective user interaction. Full article

Glucosinolate-derived metabolites play central roles in plant defense and are increasingly recognized for their pharmacological importance. Barbarea vulgaris produces a structurally diverse set of such compounds, yet their biological activities remain insufficiently explored. In this study, natural metabolites and their synthetic analogues were evaluated for antimicrobial, antibiofilm, antioxidant, and anti-inflammatory properties. Antimicrobial activity was assessed against human and plant pathogens by determining minimum inhibitory and minimum microbicidal concentrations, antibiofilm potential was examined using microplate assays, and radical scavenging activity was measured by DPPH and ABTS assays. In addition, the compounds were screened for inhibitory effects on lipoxygenase (LOX) and cyclooxygenase-2 (COX-2). Phenolic derivatives, particularly methyl-4-hydroxyphenylethyl dithiocarbamate (2) and 2-(4-hydroxyphenyl)ethyl isothiocyanate (8), exhibited notable in vitro antibacterial activity (MIC 0.312–1.25 mg mL⁻¹ against E. coli ATCC 25922 and S. aureus ATCC 25923) and detectable antibiofilm effects. Racemic barbarin (4) preferentially inhibited LOX, underscoring its potential as an anti-inflammatory scaffold, whereas COX-2 inhibition was weak across all tested compounds. None of the metabolites showed radical scavenging activity, suggesting that their effects rely on enzyme inhibition or microbial interactions rather than nonspecific antioxidant mechanisms. This study provides an integrated evaluation of B. vulgaris metabolites, highlighting their ecological role in plant defense and their potential as scaffolds for novel antimicrobial and anti-inflammatory agents. Full article

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally and are frequently dysregulated in cancer. While most studies focus on individual miRNAs, global patterns and their potential cross-kingdom similarities remain underexplored. This study aims to identify statistically stable human miRNAs in cancer, their key target genes, and analyze sequence complementarity with plant miRNAs to highlight patterns for future research. Experimentally validated human miRNA–gene interactions from miRTarBase were integrated with TCGA expression data across multiple cancers. Using a nonlinear threshold (critical threshold III), 115 underexpressed and 93 overexpressed miRNAs were identified as regulators of 200 genes with the strongest dysregulation. Further, 10,898 plant miRNAs from 127 species were computationally compared to these human miRNAs, and average complementarity scores were calculated to identify plant miRNAs most similar to under- or overexpressed human miRNAs. Statistical parameters such as membership ratios and experiment counts quantified miRNA expression stability. Subsets of human miRNAs exhibited consistent over- or underexpression across cancers, with concordant target gene expression patterns. Several plant miRNAs showed higher complementarity to underexpressed human miRNAs, suggesting reproducible cross-kingdom sequence similarity patterns. Differences in complementarity were modest but systematic, providing a computational framework for prioritizing candidate miRNAs for further study. This work establishes a computational approach integrating human miRNA–gene interactions, cancer expression data, and plant miRNA sequences. It identifies statistically stable miRNAs, key target genes, and cross-kingdom sequence similarities without implying functional or therapeutic activity. The framework can guide future experimental studies in miRNA regulation, comparative genomics, and molecular evolution. Full article