Search Results (18,842)

The dedifferentiation of smooth muscle cells (SMCs) is the main cause of atherosclerosis and vascular calcification. This study integrated the gene expression data of multiple microarrays to identify relevant marker molecules. A total of 72 Gene Expression Omnibus (GEO) samples (GSM) were collected from 10 gene expression data series (GSE) and divided into five groups: non-SMC, SMC, atherosclerotic SMC (SMC-ath), calcified SMC (SMC-calc), and treated SMC (SMC-t). The SMC-t group included synthetic SMCs that had undergone treatment to inhibit proliferation, migration, or inflammation. The gene expression data were merged, normalized, and batch effects were removed before differential gene expression (DGE) analysis was performed via linear models for microarray data (limma) and statistical analysis of metagenomic profiles (STAMPs). The genes with expressions that significantly differed were subsequently subjected to protein-protein interaction (PPI) and functional prediction analyses. In addition, the random forest method was used for classification. Twelve proteins that may be marker molecules for SMC differentiation and dedifferentiation were identified, namely, Proprotein convertase subtilisin/kexin type 1 (PCSK1), Transforming growth factor beta-induced (TGFBI), Complement C1s (C1S), Phosphomannomutase 1 (PMM1), Claudin 7 (CLDN7), Calcium binding and coiled-coil domain 2 (CALCOCO2), SAC3 domain-containing protein 1 (SAC3D1), Natriuretic peptide B (NPPB), Monoamine oxidase A (MAOA), Regulator of the Cell Cycle (RGCC), Alpha-crystallin B Chain (CRYAB), and Alcohol dehydrogenase 1B (ADH1B). Finally, their possible roles in SMCs are discussed. This study highlights the feasibility of bioinformatics analysis for studying SMC dedifferentiation. Full article

Akkermansia muciniphila—a mucus-resident commensal—has emerged as a promising target at the interface of metabolism, barrier function, and immunity. Observational human studies link higher intestinal abundance of A. muciniphila with healthier adiposity and glycemic profiles, while preclinical experiments demonstrate causal benefits on adiposity, insulin resistance, gut-barrier integrity, and inflammatory tone. These effects are attributed to mucus-layer reinforcement, reduced intestinal permeability and endotoxemia, production of short-chain fatty acids, and host signaling by defined bacterial components. In a randomized proof-of-concept trial in overweight/obese insulin-resistant adults, pasteurized A. muciniphila was safe and well-tolerated and improved insulin sensitivity and total cholesterol versus placebo; live cells showed directionally favorable but non-significant trends. A separate multicenter randomized trial of a five-strain consortium that included A. muciniphila improved post-prandial glucose and HbA1c in type 2 diabetes, supporting translational potential while underscoring the need for strain-resolved studies. Evidence for liver and cardiovascular benefits is strong in animals (e.g., MASLD and atherosclerosis models) but remains preliminary in humans. Inter-individual response heterogeneity—potentially influenced by baseline Akkermansia levels and gut-barrier status—highlights the value of personalized, microbiome-guided approaches. Larger, longer clinical studies are now warranted to define optimal dosing and formulation (live vs. pasteurized), durability, safety across populations, and impacts on hard outcomes (clinically meaningful weight change, glycemic endpoints, and cardiometabolic events). Overall, A. muciniphila represents a promising microbial adjunct for metabolic health with a plausible path from postbiotic concepts to clinical application, pending confirmatory trials. Full article

Agricultural supply chain finance plays a vital role in alleviating the financing constraints faced by agricultural business entities in developing countries and promoting inclusive and sustainable agricultural development. However, issues such as high operational risks, weak credit foundations, and insufficient risk safeguards among stakeholders in the agricultural supply chain have hindered its long-term stability. From the perspective of cooperative sustainability, this study develops a tripartite evolutionary game model involving agricultural enterprises, financial institutions, and farmers to explore the behavioral dynamics and evolutionary stability of their strategies. Using the Fuping mushroom supply chain as a case, Matlab-based simulation analysis reveals that the three-party strategy combinations failed to converge to an evolutionarily stable strategy (ESS) but instead exhibited dynamic changes characterized by non-periodic oscillations. Sensitivity analysis further demonstrates that farmers’ credit behavior is a key determinant of the sustainable operation of the supply chain financing system, while enhancing enterprises’ guarantee willingness can effectively mitigate farmers’ default risk. Moreover, stronger cooperative relationships between enterprises and farmers improve the overall resilience and stability of the system. The findings provide practical insights for building sustainable and resilient agricultural financial ecosystems, emphasizing the need to introduce third-party guarantee institutions, strengthen credit constraint systems, and design incentive mechanisms that promote long-term cooperation among stakeholders. Full article

Comprehensive highway scene understanding and robust traffic risk inference are vital for advancing Intelligent Transportation Systems (ITS) and autonomous driving. Traditional approaches often struggle with scalability and generalization, particularly under the complex and dynamic conditions of real-world environments. To address these challenges, we introduce a novel structured prompting and multi-agent collaborative knowledge distillation framework that enables automatic generation of high-quality traffic scene annotations and contextual risk assessments. Our framework orchestrates two large vision–language models (VLMs): GPT-4o and o3-mini, using a structured Chain-of-Thought (CoT) strategy to produce rich, multiperspective outputs. These outputs serve as knowledge-enriched pseudo-annotations for supervised fine-tuning of a much smaller student VLM. The resulting compact 3B-scale model, named VISTA (Vision for Intelligent Scene and Traffic Analysis), is capable of understanding low-resolution traffic videos and generating semantically faithful, risk-aware captions. Despite its significantly reduced parameter count, VISTA achieves strong performance across established captioning metrics (BLEU-4, METEOR, ROUGE-L, and CIDEr) when benchmarked against its teacher models. This demonstrates that effective knowledge distillation and structured role-aware supervision can empower lightweight VLMs to capture complex reasoning capabilities. The compact architecture of VISTA facilitates efficient deployment on edge devices, enabling real-time risk monitoring without requiring extensive infrastructure upgrades. Full article

In mineral processing and metallurgy, total iron grade serves as a critical indicator guiding the entire production chain from crushing to smelting, directly influencing the quality and yield of steel products. To address the limitations of conventional matrix effect correction methods in X-ray fluorescence (XRF) analysis—such as low accuracy, high time consumption, and labor-intensive procedures—this study proposes a novel hybrid model (DSCN-LS) integrating least squares (LS) with dynamically regularized stochastic configuration networks (DSCNs) for total iron ore grade quantification. Through feature analysis, we decompose the grade modeling problem into a linear structural component and nonlinear residual terms. The linear component is resolved by means of LS, while the nonlinear terms are processed by the DSCN with a dynamic regularization strategy. This strategy implements node-specific weighted regularization: weak constraints preserve salient features in high-weight-norm nodes, while strong regularization suppresses redundant information in low-weight-norm nodes, collectively enhancing model generalizability and robustness. Notably, the model was trained and validated using datasets collected directly from industrial sites, ensuring that the results reflect real-world production scenarios. Industrial validation demonstrates that the proposed method achieves an average absolute error of 0.3092, a root mean square error of 0.5561, and a coefficient of determination (R²) of 99.91% in total iron grade estimation. All metrics surpass existing benchmarks, confirming significant improvements in accuracy and operational practicality for XRF detection under complex industrial conditions Full article

The Dutch horticultural supply chain is characterised by substantial uncertainty resulting from ongoing organisational changes, such as the transformation from an auction-cooperative system to a sales organisation-based structure. This uncertainty causes strategic behaviour among all supply-chain members (including producers), which often disadvantages primary producers. This study investigates how uncertainty shapes trading behaviour and decision-making using Transaction Cost Theory as a theoretical framework. Specifically, it examines the relationship between environmental and behavioural uncertainty, trading behaviour and strategic responses. Employing a multimethod approach involving interviews, simulation sessions and debriefings to collect data, this study integrates a qualitative and quantitative analysis. The findings reveal: (1) how uncertainty influences trader behaviour and strategic decision-making, and demonstrates the need for more effective coordination mechanisms and strategies to reduce opportunism and inefficiencies in horticultural trade, (2) the diversity of strategic responses to uncertainty and (3) the factors that influence uncertainty and their relationship. Thes factors, include the current supply-chain structure that upholds uncertainty and strategic behaviour such as the deliberate exploitation of the absence or lack of information (asymmetric information). By combining methodological triangulation with theoretical insight, this study provides a foundational understanding of strategic behaviour under uncertainty in agri-food supply chains. Full article

In recent years, unmanned aerial vehicle (UAV) technology has been increasingly widely used in natural disaster rescue. To enable fast and accurate localization of rescue targets in disaster environments, this paper proposes a multi-level coordinate system transformation method for quadrotor UAVs based on monocular camera position compensation. First, the preprocessed image object is transformed from pixel coordinates to camera coordinates. Second, to address the issue that coupling errors between the camera and UAV coordinate systems degrade the accuracy of coordinate conversion and target positioning, a Static–Dynamic Compensation Model (SDCM) for UAV camera position error is established. This model leverages a UAV attitude-based compensation mechanism to enable accurate conversion of camera coordinates to UAV coordinates and north-east-down (NED) coordinates. Finally, according to the Earth model, a multi-level continuous conversion chain from the target coordinates to the Earth-centered–Earth-fixed (ECEF) coordinates and the world-geodetic-system 1984 (WGS84) coordinates is constructed. Extensive experimental results show that the accuracy of the overall positioning method is improved by approximately 23.8% after completing our camera position compensation, which effectively enhances the positioning performance under the basic method of coordinate transformation, and provides technical support for the rapid rescue in the post-disaster phase. Full article

Occupational exposure to soil-borne pesticides remains a critical safety and process-management challenge in industrial and agro-industrial settings. This work proposes a process-integrated analytical workflow that couples comparative instrumental identification of soil xenobiotics with an occupational risk assessment framework. We comparatively evaluate GC-MS (gas chromatography–mass spectrometry), HPLC (high performance liquid chromatography), FTIR (Fourier-Transform Infrared Spectroscopy), LC-MS/MS (Liquid Chromatography coupled with tandem Mass Spectrometry), and ICP-MS (Inductively Coupled Plasma Mass Spectrometry) against matrix complexity, sensitivity, cost, and throughput, and implement the Quick, easy, cheap, effective, rugged, safe (QuEChERS) method-based sample preparation followed by GC-MS and LC-MS/MS to demonstrate applicability on representative soil and food-chain samples. Complementary risk tools (toxicity–probability matrices, exposure pathway diagrams) and an integrated monitoring scheme that combines environmental data with biomonitoring are used to link concentrations to exposure potential and control priorities. In a soil case sample, low-level organochlorines were detected with total DDT at 0.010 mg/kg and total HCH at 0.003 mg/kg, illustrating how analytical outputs feed decision matrices for prioritizing interventions. Case analyses from agricultural and industrial contexts indicate that targeted substitution, optimized application, ventilation and dust control, PPE (personal protective equipment) adherence, and worker training can measurably reduce symptoms and biomarkers of exposure. Overall, a complementary, process-analytical approach—integrating sensitive multi-technique detection with exposure assessment and continuous monitoring—supports proactive risk management and aligns with process systems and monitoring themes. Recommendations include standardizing workflows, coupling routine environmental monitoring with biomonitoring where feasible, and embedding preventive policies and training into industrial management systems. Full article

Maritime accidents are low-probability, high-consequence events, making mechanism analysis crucial for risk mitigation. Existing studies often focus on single scenarios or factors and frequently mix pre-incident observational data with subjective unsafe behavior labels, limiting causal-chain construction for proactive risk prediction. To address these issues, this study proposes a Bow-Tie-based causal-chain Bayesian network, establishing a hierarchical inference chain of “observed parameters–unsafe causes–accident types” to capture causal interactions among multiple factor categories and enable inference from pre-incident data to potential unsafe causes and accident types. Applied to the Bohai Sea region, sensitivity analysis quantified the effects of risk factors under varying conditions on collision, sinking, and grounding probabilities. The results show that the method can infer accident types and unsafe causes using only pre-incident data, achieving over 70% accuracy and closely matching accident investigation findings. Moreover, it reveals layer-by-layer mechanisms of key contributing factors and provides targeted management interventions, supporting quantitative decision-making for maritime regulators and shipping companies, with significant practical applicability. Full article

Scaffolds are widely recognized as implantable alternatives in the field of tissue engineering. Among various scaffold structures, grid structures are commonly used due to their simple design and ease of fabrication. However, grid structures have a critical demerit of low mechanical stiffness compared to its own mechanical property (used material’s compressive stiffness), as the limited contact area between strands prevents effective load distribution. Several structural designs, such as triply periodic minimal surface (TPMS), modified honeycomb, and Kagome structures, have been proposed to improve compressive stiffness. Despite their mechanical advantages, these structures are limited by complex design and manufacturing processes. In this study, we propose a Bead-Chain-Shaped (BCS) scaffold, which maintains the simplicity of grid structures while enhancing compressive stiffness through the printing process alone. To optimize the printing process and enhance fabrication efficiency, we developed an artificial intelligence (AI)-based process optimization model that correlates printing parameters (pressure, printing speed, and delay time) with the resulting geometric accuracy while maintaining the designed geometry, and predicts the optimal printing conditions for the predesigned Bead-Chain-shaped (BCS) geometry. The model was then used to extract these optimal printing conditions, enabling precise dimensional control and improving overall fabrication accuracy of the Bead-Chain-Shaped (BCS) scaffold dimensions. Under the optimized printing conditions, the BCS scaffolds achieved compressive stiffness values of 61.8, 75.9, and 91.6 MPa for BCS 5545, 6040, and 6535, respectively, corresponding to increases of 11.9%, 37.3, and 65.7% compared to the control scaffold (55.3 MPa). Numerical analysis confirmed that compressive stiffness increases as strand-to-strand contact area increases. Furthermore, in vitro cell proliferation assays demonstrated no significant difference in cell proliferation compared to conventional structures (grid-structure scaffold), indicating that the proposed design does not inhibit cellular growth. These results highlight the potential of the proposed Bead-Chain-Shaped (BCS) scaffold as a promising candidate for bone tissue engineering, offering both enhanced mechanical stiffness and fabrication efficiency. Full article

Silicone rubber, primarily composed of polydimethylsiloxane (PDMS) chains, is widely used in sealing materials due to its excellent flexibility and durability. Its performance is significantly affected by environmental conditions, with humid-heat aging being a major factor of degradation. In this study, molecular dynamics simulations were conducted to systematically investigate the effects of water and temperature on PDMS at the molecular scale. The glass transition temperature (T_g) and free volume distribution were analyzed to evaluate the mobility of polymer chains under hydrated conditions. Mechanical simulations (including tensile and compressive deformation) indicate that the combined effect of elevated temperature and moisture significantly accelerates the degradation of rubber properties. Thermal decomposition simulations indicate that, under high-temperature and humid conditions, PDMS main chains gradually break into small molecules, with free radical reactions further promoting the aging process. The results elucidate the molecular mechanisms underlying silicone rubber performance deterioration under the coupled action of water and temperature, providing a theoretical basis for service-life prediction and durability design of sealing materials. Full article

Biodiversity loss poses a threat to corporate performance and social welfare. Biodiversity disclosure enables investors to evaluate firms’ biodiversity status. However, it remains unclear whether and how biodiversity disclosure affects capital market efficiency. In this paper, we employ a binary variable derived from a word-frequency analysis of annual reports to determine whether a firm has disclosed biodiversity information. Using a panel of Chinese listed companies from 2011 to 2022, we provide robust evidence that Companies that disclose biodiversity information have experienced sustained improvements in stock liquidity. Furthermore, the effect is significantly amplified after the 2020 UN Biodiversity Summit, suggesting that investors respond positively to biodiversity disclosure. Channel analysis reveals that higher inventory turnover reinforces this positive effect, while greater financing constraints and higher management ownership weaken it. Heterogeneity analysis further indicates that this effect is more pronounced among firms with higher environmental information asymmetry, lower supply chain transparency, and lower patient capital. This study sheds light on how biodiversity disclosure affects market efficiency and offers important insights for future research and policy. Full article

Ultraviolet B (UVB) light exerts biological effects beyond the skin; however, its influence on systemic energy metabolism remains unclear. We investigated the effects of chronic, low-dose narrowband UVB irradiation on substrate utilization, circulating metabolites, and thermogenesis of brown adipose tissue (BAT) in mice. Male and female C57BL/6J mice were daily exposed to sub-erythemal UVB (308 nm, 50 or 100 mJ/cm², 3 h) for up to 7 weeks using a custom light-emitting diode-based device. Metabolic outcomes were assessed by indirect calorimetry, locomotor activity monitoring, and infrared thermography. Plasma metabolites were profiled by capillary electrophoresis–time-of-flight mass spectrometry. Gene expression in BAT and skin was measured by reverse transcription quantitative polymerase chain reaction. UVB exposure lowered the respiratory exchange ratio at specific time points, indicating greater lipid utilization, and transiently increased oxygen consumption. Metabolomic profiling revealed reduced succinate levels and enrichment of nicotinate/nicotinamide and propanoate metabolism pathways. Infrared thermography showed elevated surface temperature after irradiation and that prolonged UVB exposure modestly upregulated thermogenic genes in BAT, along with increased cutaneous expression of Cidea. These findings suggested that sub-erythemal UVB exposure modestly modulates systemic metabolism, circulating metabolites, and BAT activity, highlighting UVB as a potential environmental regulator of energy balance. Full article

Background: In China, a paradox has emerged: while the digital access gap narrows, a pronounced digital gradient—a sequential decline in outcomes from urban to county to township students—persists in innovation and entrepreneurship. This study investigates the hidden, cognitive mechanisms behind this enduring gradient inequality. Methods: Analyzing a national survey of 31,779 students, we employed statistical models designed to trace sequential pathways and account for institutional influences. Results: We found a clear urban > county > township gradient in students’ digital literacy, information perception, and innovation capabilities. The disparity is primarily driven by a cognitive mediation chain: rural students’ lower digital literacy inhibits their ability to perceive and evaluate information effectively, which in turn suppresses their innovation and entrepreneurial potential. This “digital literacy → information perception” pathway explains over 80% of the gap in entrepreneurial intention and one-third of the gap in innovation capacity. Crucially, elite “Double First-Class” universities mitigate this gradient; their robust offline support systems compensate for deficits in students’ digital literacy, reducing its necessity for entrepreneurial success. Conclusions: The contemporary digital divide is fundamentally a cognitive gradient. Moving forward, policy must look beyond infrastructure to foster a cognitive capacity to transform digital access into innovation capability, rather than merely expanding digital access. Our findings affirm that universities can act as powerful institutional compensators. A dual strategy that combines cognitive empowerment with targeted institutional support is essential to bridge the digital gradient and close the innovation gap across urban, county, and township student populations. Full article

Sulfoxaflor, an insecticide, acts on nicotinic acetylcholine receptors. It has a functional group similar to that of neonicotinoid insecticides, which are testicular toxicants. Recently, the adverse effects of sulfoxaflor on the testes have been reported in rats. This study aimed to address the lack of reports on sulfoxaflor administration in mice and its effects on the testes. ICR mice (3- and 10-week-old) were treated ad libitum with two different concentrations (10 and 100 mg/kg) of sulfoxaflor for 4 and 8 weeks. Histological analysis and real-time reverse transcription polymerase chain reaction were performed. Testis weights relative to body weights in the sulfoxaflor groups showed no significant difference compared to the control group. Testicular tissue in the sulfoxaflor groups was unchanged compared to that in the control group. The sulfoxaflor-treated group showed no significant differences in the mRNA expression of luteinizing hormone and follicle-stimulating hormone in the pituitary gland compared to the control group. Furthermore, no significant differences were noted in the mRNA expression levels of various gene markers in the testes between the sulfoxaflor-treated and control groups. These markers include those related to Leydig cells, testosterone synthesis, Sertoli cells, proliferating cells, meiotic cells, pachytene spermatocytes, round spermatids, apoptotic cells, antioxidant enzymes, oxidative stress factors, and mitochondrial function. In contrast to findings in rats, which showed testicular toxicity, sulfoxaflor administration at low concentrations did not adversely affect intratesticular cells in either mature or immature mice at the doses and time points examined. In the future, we would like to conduct research on high concentrations of sulfoxaflor by changing the administration method. Full article