Search Results (64,551)

Background: Three-dimensional (3D) cell cultures are increasingly recognized as effective models for studying diseases and developing cell therapies. In the endocrine pancreas field, organoids/spheroids derived from human islet cells enable advances in diabetes research, drug screening, and tissue engineering. While various 3D culture methods exist, approaches such as magnetic bead-assisted aggregation remain underexplored for endocrine pancreatic cells. Additionally, the use of biological scaffolds, especially those derived from decellularized pancreatic extracellular matrix, provides a biomimetic environment that promotes adhesion, proliferation, and functionality of pancreatic cells. This study presents a protocol for magnetic bead-guided 3D culture of human islet cells within decellularized pancreatic scaffolds. Methods: Human pancreas from adult brain-dead donors was harvested for both islets’ isolation processing and decellularization to generate an acellular pancreatic bioscaffold. Primary human pancreatic islets were first grown in two-dimensional adherent cultures, then enzymatically harvested from the surface and reassembled into three-dimensional clusters using different initial cell amounts (small clusters 0.5 × 10⁴–1 × 10⁴ and larger clusters 2.5 × 10⁴–5 × 10⁴ cells) and then placed within acellular pancreatic slices of different thickness, namely 50 and 90 μm. Optic microscopic examination, scanning electron microscopy analysis, and assessment of insulin and lactate dehydrogenase (LDH) levels were used to evaluate these 3D islet-like cluster cultures. Results: We report the establishment of 3D cultures derived from primary pancreatic islet cells using a magnetic approach in a remarkable 18 h period for the complete formation of 3D clusters. The small clusters (0.5 × 10⁴–1 × 10⁴ cells) exhibited a faster attachment to the acellular matrix, with cells visibly spreading outside the cluster interacting with the bioscaffold slice, when compared to the larger clusters (2.5 × 10⁴–5 × 10⁴ cells). These cells continued to produce insulin, and no statistically significant differences in LDH levels were found under these different conditions. Conclusions: Here, we demonstrate that a magnetic bead-based protocol can be successfully applied to endocrine pancreatic cells, enabling the rapid formation of compact, viable, and functional 3D structures. Despite limitations such as higher cost and prolonged retention of magnetic particles, the approach supports size-dependent interactions with decellularized pancreatic scaffolds. These findings are valuable for researchers designing experiments tailored to specific objectives and underscore the potential of this platform for advancing diabetes research and pancreatic tissue engineering. Full article

Although the central focus of ecology has long been the relationship between biodiversity and ecosystem functioning, this relationship has rarely been explored in species-poor communities such as salt marshes, which have the potential to shed new light on this debate. We conducted two microcosm experiments, each testing a different environmental variable (salinity or disturbance) and its interaction with the plant community’s richness and species composition, using all possible combinations of the three sedge species found in the pioneer plant community in the Yangtze River Estuary. The relationships between diversity and productivity were weak and non-significant, possibly due to intense competition among the sedges. Species composition played a more important role in determining productivity. Moreover, biodiversity effects were found to be environment-dependent. Salinity stress increased the selection effect, while disturbance tended to increase both selection and complementarity effects. Interestingly, the correlation between biodiversity and stability was non-linear and presented different patterns in the salinity and disturbance experiments. Our results show that species-poor systems with low functional group diversity may exhibit weak relationships between biodiversity and ecosystem functioning during the establishment phase under controlled experimental conditions. In this ecosystem, species richness rarely impacted biomass, which was instead primarily driven by species composition and environmental conditions. Full article

In two-phase flow, the interaction between multi-scale vortex structures and interfaces (bubbles or free surfaces) triggers a range of complex physical phenomena. This study employs numerical simulations to investigate the interaction between a horizontal vortex and the interface separating two layers of immiscible fluids with different densities (e.g., water and air). The vortex is initialized as an internal motion within the heavier phase. We focus specifically on the impact of the phase density ratio and surface tension. Numerical simulations reveal that when the density ratio is near unity, interface rupture occurs only at high Weber numbers (We), where low surface tension enables the rupture of sharp interface points. Conversely, at high surface tension (low We), these sharp points stretch into thin liquid films, significantly increasing the surface area without causing breakage. As the density ratio increases, interface rupture at sharp points accelerates, even under high surface tension, leading to faster dissipation of the initial vortex. In high-We scenarios, an increased density ratio promotes the faster formation and greater intensity of new vortex layers at the interface. However, increasing surface tension enhances the vorticity of these layers but simultaneously slows their generation rate. The findings highlight the critical interplay between surface tension and density differences in vortex–interface interactions, with surface tension stabilizing the interface and density differences driving more intense vortex shedding and deformation. These insights offer valuable guidance for understanding two-phase flow behavior and improving the design of systems involving multiphase fluids. Full article

Identifying the multi-scale drivers of ecosystem service (ES) trade-off intensity is essential for promoting regional sustainability. However, the existing multi-scale ES studies typically rely on predefined administrative units or fixed grid sizes due to the absence of scientifically sound scale-partitioning approaches, which limits the identification of characteristic scales and obscures scale-dependent interactions. This study broke new ground by combining continuous wavelet transform (CWT) and optimal parameter geographic detector (OPGD) to automatically identify the characteristic scales of trade-offs between ecosystem services, thus opening up a new avenue in multi-scale studies. Taking China’s plain–mountain transition zone as a case study, we evaluate trade-off intensity among four key ecosystem services—water yield (WY), habitat quality (HQ), soil conservation (SC), and carbon storage (CS). The results show that the following: (1) The identification of 36 characteristic scales (ranging from 5 km to 55 km) indicates that ecosystem service trade-offs operate across a wide range of spatial extents, implying that a single management scale cannot effectively address all ES interactions. (2) From 2000 to 2020, CS-HQ, SC-HQ, and WY-HQ trade-off intensities were jointly driven by both natural conditions and human activities, whereas CS-SC was predominantly influenced by natural and climatic factors. The trade-off intensities between CS-WY and WY-SC were mainly controlled by climatic forces. (3) The explanatory power (q value) of each factor varied distinctly with spatial scale, and the interaction effects between multiple factors were substantially stronger than their individual effects. This indicates that ecosystem service trade-offs are primarily governed by coupled processes rather than isolated drivers. Consequently, management strategies targeting single drivers are unlikely to be effective. Instead, ecosystem management should be designed around combinations of drivers that operate at specific spatial scales and provide a concrete pathway for translating trade-off analyses into spatially differentiated management actions. Full article

To address the challenge that traditional dam model materials are difficult to simultaneously meet the requirements of microstructural similarity, dynamic damage simulation, and environmental friendliness, a novel microparticle mortar simulated concrete was developed. This new material consists of cement, sand, gypsum, mineral oil, water, and baryte sand. Through systematic material mechanical tests, the effects of each component on the material’s strength, density, and elastic modulus were revealed, and the optimal mix ratio was determined. This enabled precise control of low elastic modulus and had a high density, while the material is environmentally friendly, non-toxic, and compatible with direct contact with natural water. Its mechanical properties are highly similar to those of the prototype concrete. Based on a 1:70 geometric scale, a shaking table model test of the concrete gravity dam-reservoir system was conducted. The dynamic response and damage evolution under empty and full reservoir conditions were compared and analyzed. The study shows that this material can accurately simulate the stress-strain relationship and failure mode of prototype concrete. Under the full reservoir condition, the dam’s fundamental frequency showed only a 2.72% deviation from the numerical simulation, and as the seismic excitation amplitude increased, the changes in the fundamental frequency effectively reflected the accumulation of damage. Under the design seismic motion, the measured accelerations and stress responses for both empty and full reservoir conditions were in good agreement with numerical calculations. Under overload conditions, the acceleration amplification factor at the dam crest decreased with damage accumulation, and the dam neck was identified as the seismic weak zone. As the peak ground acceleration (PGA) increased from 0.15 g to 0.70 g, the fundamental frequency changes effectively reflected the damage accumulation process in the dam, while the hydrodynamic pressure at the dam heel showed a linear increase (457% increase). The experimentally measured hydrodynamic pressure distribution was between the rigid dam and elastic dam hydrodynamic pressures, reflecting the real fluid-structure interaction effect. This study provides a reliable material solution and data support for dam seismic physical model testing. Full article

In response to the widespread adoption of hybrid work models, organizations must strategically address the challenges of knowledge transfer and organizational learning in distributed environments. We extend March’s computational model of organizational learning by initially incorporating three variables: the ratio of tacit-to-explicit knowledge, the proportion of remote workers, and structured shift arrangements. The extended model incorporates distinct subgroups for remote and on-site workers, organizational memory mechanisms for tacit knowledge exchange, and alternating work location schedules designed to foster interaction. Simulation results reveal that under non-contact scheduling, the interaction effect between learning from code/memory ($p_1$) and the proportion of tacit knowledge ($q$) is insignificant, while the coefficient of interaction effect $p_2\times q$ between learning by code/memory ($p_2$) and $q$ is twice that under partial-contact or full-contact scheduling. Moreover, under full-contact scheduling, the interaction effect between $p_1$ and the proportion of work-from-home employees ($wfh$) is insignificant ($p>0.1$), whereas the interaction effect between $p_2$ and $wfh$ is significant ($p<0.05$). Aligning with March’s findings that a low $p_1$ and high $p_2$ contribute to higher organizational knowledge, our simulation results indicate that non-contact scheduling preserves knowledge diversity, and full-contact scheduling promotes small-world network effects, thereby enhancing organizational knowledge equilibrium. These findings position hybrid work scheduling as a data-driven managerial decision, and the proposed model offers analytical insights for optimizing knowledge processes within business analytics contexts. Full article

Background/Objectives: Synovial sarcoma (SS) is a rare and aggressive soft-tissue malignancy characterized by complex molecular alterations and poor prognosis, highlighting the need for targeted immunotherapeutic strategies. This study aimed to design a rational multi-epitope vaccine targeting the FKBP10 oncoprotein to elicit effective immune responses against SS. Methods: Transcriptomic data from the GEO dataset GSE144190, comprising 10 tumor and 9 normal tissue samples, were analyzed to identify differentially expressed genes (DEGs). Results: Our findings revealed significantly upregulated FKBP10 with a log2 fold change of 3.55, baseMean expression of 1521.84, and adjusted p-value of 8.37 × 10⁻²⁶. Mutational analysis across 7782 sarcoma samples indicated a low alteration frequency of ~1.5%, primarily missense variants. Functional mapping showed FKBP10 as a hub interacting with multiple collagen chains and chaperone proteins, implicating its role in extracellular matrix organization and protein folding. Linear B-cell epitope prediction identified 17 epitopes (6–21 amino acids), while T-cell mapping yielded 10 MHC class I and 9 MHC class II high-affinity epitopes, all antigenic (VaxiJen > 0.5) and non-allergenic. A multi-epitope vaccine was constructed incorporating a 50S ribosomal protein L22 adjuvant, linkers, and a 6× histidine tag. Physicochemical analysis showed a molecular weight of 36.43 kDa, pI 6.97, instability index 31.79, aliphatic index 64.88, and GRAVY −0.509, indicating stability and hydrophilicity. Structural modeling validated 82.5% residues in favored regions. Molecular docking revealed strong binding with TLR4 (−9.7 kcal/mol) and TLR9 (−9.4 kcal/mol), and 200 ns molecular dynamics simulations confirmed stable RMSD trajectories, low RMSF at binding residues (<4 Å), persistent hydrogen bonding, compact radius of gyration (38–42 Å for TLR4; ~20 Å for TLR9), favorable total energy (−1400 to −1500 kcal/mol for TLR4; −650 to −720 kcal/mol for TLR9), and stable SASA (~52,000–54,000 Ų). Conclusions: These findings demonstrate that the FKBP10 multi-epitope vaccine is structurally stable, immunogenic, and capable of engaging key innate immune receptors, supporting its potential as a promising immunotherapeutic candidate for synovial sarcoma. Full article

Precision nutrition has emerged as a promising strategy for the prevention of type 2 diabetes mellitus (T2DM) by targeting molecular pathways underlying insulin resistance and impaired glucose metabolism. Accumulating evidence indicates that dietary patterns, caloric intake, and specific nutrients can modulate gene expression and epigenetic mechanisms involved in insulin signaling, inflammation, and energy homeostasis. This narrative review synthesizes recent human and experimental studies (2025–2026) examining how dietary components influence transcriptional and epigenetic regulation of insulin signaling and glucose metabolism in the context of T2DM prevention. A total of 29 peer-reviewed studies were included, encompassing dietary patterns, macronutrient manipulation, micronutrient and bioactive supplementation, and gene–diet interactions. Very-low-calorie diets consistently induced coordinated modulation of key metabolic genes, including downregulation of glucose transporter type 4 (GLUT4) and upregulation of PDK4, CPT1, and AMPK, reflecting a metabolic shift toward enhanced fatty acid oxidation and improved insulin sensitivity. In contrast, high-fat and fructose-rich diets promoted proinflammatory gene expression and immune activation, contributing to insulin resistance. Plant-based and vegan dietary patterns were associated with reduced epigenetic aging and improved insulin sensitivity through DNA methylation changes. Targeted interventions, including vitamin D combined with probiotics, dietary fiber, nucleotides, and trace elements such as copper, further demonstrated favorable transcriptional and epigenetic effects linked to improved glycemic control. Collectively, these findings highlight diet-driven modulation of insulin signaling and glucose metabolism at the molecular level and support nutrigenomics-guided precision nutrition as a viable preventive approach for T2DM. Integrating genetic and epigenetic insights into dietary strategies may enable more personalized and effective interventions to curb the growing global burden of type 2 diabetes. Full article

The accurate prediction of extreme dynamic amplification factor (DAF) values is significantly important to ensure a long-term safety assessment of bridges under stochastic vehicular loading. However, predicting extreme DAFs is challenging due to traffic randomness, road roughness variability, and nonlinear vehicle–bridge interaction (VBI) effects. This study presents an integrated framework for extreme DAF prediction for simply supported bridges by combining stochastic traffic–bridge interaction simulations with Bayesian updating and a Peaks-Over-Threshold–Generalized Pareto Distribution (POT–GPD) model. A coupled VBI model is developed, incorporating cellular automaton-based traffic flow, multi-axle nonlinear vehicle dynamics, finite-element bridge modeling, and stochastic road roughness profiles. A new DAF definition based on dynamic displacement difference is proposed to better represent dynamic effects. DAF samples obtained from VBI simulations under different road roughness levels are analyzed using the POT method, with GPD parameters estimated through maximum likelihood and Bayesian inference. Extreme DAFs corresponding to different return periods are then determined. The results indicate that extreme DAF values increase with worsening road roughness and longer return periods and that the Bayesian POT–GPD approach effectively captures tail behavior while providing reliable uncertainty quantification for extreme DAF prediction. Full article

This study addresses the major engineering challenges of leaving roadways along the goaf in shallow-buried coal seam tunnels through water-bearing soft rock. It focuses on three core issues: the mechanism of rock mass softening upon water exposure, large-deformation control, and directional pressure relief technology. By integrating laboratory testing, theoretical analysis, numerical simulation, and field testing methods, the evolution of macro- and micro-mechanical properties of rock under water–rock interaction can be studied. The research developed constant-resistance large-deformation rock bolts with “yielding within resistance and resisting within yielding” characteristics, revealed the mechanism of directional fracturing through shaped charge blasting, and proposed a synergistic control technology for along-the-goal rib retention: “shaped charge blasting for roof fracturing and pressure relief + reinforced rib support + debris retention devices.” Research findings indicate: increased sandstone water content triggers dissolution of calcareous cement and expansion of clay minerals, leading to rock strength degradation and accelerated deformation, yet the failure mode remains uniaxial shear failure. The developed constant-resistance large-deformation anchor core device maintains a stable working resistance of approximately 350 kN within a 396–405 mm tensile deformation range, significantly enhancing the support system’s crack-resistant capacity under pressure. The focused jet directs cracks to penetrate along predetermined paths, forming planar damage zones and effectively suppressing vertical damage to the surrounding rock. Based on field monitoring, the tunnel was divided into advance support zones, temporary support zones, and stable tunnel sections, enabling a differentiated support scheme. The engineering application achieved stable tunnel retention and safe reuse. This study provides key theoretical foundations and technical approaches for controlling rock mass stability in similar tunnel conditions. Full article

Expanding Coffea canephora cultivation to transitional altitudes offers a promising strategy to sustain coffee production under climate change. This study evaluated 27 genotypes cultivated under two water management regimes (fully and minimally irrigated) at 650 m altitude in Espírito Santo, Brazil, over eight harvests (2018–2025). A split-plot design was analyzed using a three-way mixed model (REML/BLUP) to estimate genetic parameters and predicted genotypic values. Adaptability and stability were assessed using the harmonic mean of relative performance of genotypic values (HMRPGV) and weighted average of absolute scores (WAASB) and integrated into a multi-trait selection index. Significant genotypic and temporal effects were detected, while the interaction between genotypes and water management regimes was non-significant, indicating consistent performance under different water regimes. Broad-sense heritability was moderate, with high selective accuracy. Genotypes 108 and 203 achieved the highest predicted yields (91.4 and 86.8 bags ha⁻¹) and superior adaptability. The multi-trait index identified six outstanding genotypes—108, 203, 201, 306, 303, and 302—combining high yield, broad adaptability, and temporal stability, resulting in an expected genetic gain of 8.17% in relation to the original population. These findings demonstrate that selected C. canephora genotypes are well adapted to transitional altitudes, supporting breeding programs for climate-resilient and high-yielding crops. Full article

The objective of this study was to evaluate the individual and synergistic antimicrobial efficacy of Juniperus excelsa berry essential oil (JEO) and the cell-free supernatant (CFS) from Streptococcus thermophilus against Escherichia coli (ATCC 43888), Staphylococcus aureus (ATCC 25923), and multidrug-resistant Salmonella enterica serovar Infantis S2 isolated from chicken meat. In vitro antimicrobial effects were assessed using the agar well diffusion and microdilution methods (MIC and MBC assays). The in vivo antimicrobial effect of these natural bioactive substances in controlling microbial growth in chicken meat stored at 4 °C for 48 h was also evaluated. Bioactive components of JEO were determined via GC–MS, identifying alpha-pinene (84.56%) as the primary compound. In vitro assays revealed that JEO showed high antimicrobial activity against Gram-positive S. aureus with a zone diameter of 35.50 mm (p < 0.05). JEOCFS treatment, which is the combination of CFS and JEO, demonstrated a significant synergistic interaction against S. aureus, resulting in an MIC value of 25 mg/mL. CFS alone exerted a measurable inhibitory effect on S. aureus, with an MIC of 50 mg/mL, indicating its potential antimicrobial capability. Further evaluation of the in vivo antimicrobial efficacy using chicken meat stored at 4 °C revealed that the JEOCFS treatment significantly inhibited microbial growth (p < 0.05). After 48 h of storage under refrigerated conditions, the number of psychrophilic bacteria in the control group reached 8.40 log cfu/g, while it remained significantly lower at 6.44, 5.37, and 6.74 log cfu/g in the JEO, JEOCFS, and CFS treatments, respectively. These results indicate that the synergistic application of JEO and CFS effectively suppresses foodborne pathogens, particularly S. aureus, and extends the microbiological shelf life of refrigerated chicken meat. Full article

The rapid aging of bridges has increased interest in real-time, data-driven monitoring for predictive maintenance and safety management; however, practical deployment on in-service bridges remains limited. This paper presents lessons learned from long-term field deployment of real-time bridge joint monitoring systems on three in-service highway bridges and demonstrates how these insights can support the transition toward Industry 5.0. A unified framework is introduced to integrate key enabling technologies, including Internet of Things (IoT), digital twins, and artificial intelligence (AI), into a practical, human-centric monitoring architecture. Best practices for achieving durable, site-compliant, and cost-effective system design are summarized, with emphasis on sensor selection, wireless communication strategies, modular system development, and maintaining seamless operation. The development of a Docker-based analytics and visualization platform illustrates how interactive dashboards enhance human–machine collaboration and support informed decision-making. The role of advanced analytical tools, including digital twins, AI, and statistical modeling, in providing reliable structural assessments is highlighted, along with guidance on balancing cloud and edge computing for energy-efficient performance under constraints such as limited power, weather exposure, and site accessibility. Overall, the findings support the development of scalable, resilient, and human-centric real-time monitoring systems that advance data-driven decision-making and directly contribute to the realization of Industry 5.0 objectives in bridge health management. Full article

Polymer nanocomposites have been attracting significant interest over the last three decades. One of the most intriguing applications is related to the preparation of clay-filled nanocomposites based on rubber blend matrices. Although several studies already exist on the subject, there is limited information available regarding their rheological, thermal, and, particularly, damping behaviour of rubber blend systems. In this work, the rheological, viscoelastic, and thermal behaviour of a natural rubber/nitrile rubber (NR/NBR) blend nanocomposite containing organically modified nanoclay was systematically investigated, and the damping characteristics were also assessed. At a lower nanoclay concentration (5 phr), network formation through filler–filler and filler–polymer interactions led to partial immobilization of polymer chains, resulting in a pronounced increase in viscosity and enhanced viscoelastic response. In contrast, at higher nanoclay loading (10 phr), strong agglomeration of filler particles occurred, corresponding to a stacked clay morphology, which hindered effective filler–filler network formation and weakened filler–polymer interactions, leading to lower viscosity and reduced damping efficiency. The blend composition and filler content were found to significantly influence the investigated properties, especially the hysteresis loss and the thermal conductivity, which is explained by matrix–filler interactions and the resulting morphology of the system. Full article

Nicotine vaping has surged in recent years, particularly among young adults, and is strongly linked with concurrent alcohol use. Separately, chronic excessive alcohol use drives hypertension and cardiomyopathy, while nicotine vaping is linked to a modest rise in cardiovascular disease incidence and mortality. However, little is known about how concurrent use interacts to affect protein expression in the cardiovascular system. The aim of this study was to determine differential cardiac protein expression in mice exposed to concurrent chronic-plus-binge alcohol and nicotine vaping use. Male C57BL6/J mice received a 20-day 5% ethanol diet with 5 g/kg ethanol binges on days 10 and 20, alongside isocaloric controls. During this period, they were also exposed nightly to either 5% nicotine salt vapor, vegetable glycerin/propylene glycol vehicle vapor, or room air. The left ventricular free wall was collected and analyzed using discovery-based proteomics and subsequent Ingenuity Pathway Analysis. A total of 3144 proteins were identified across all groups. Compared to air-exposed, control-fed mice, 201 proteins were significantly altered by ethanol, 101 proteins by nicotine vaping, and 159 proteins by combined exposure. Both ethanol and nicotine vaping influenced pathways involved in lipid homeostasis, extracellular matrix remodeling, and mitochondrial bioenergetics; however, these alterations did not uniformly manifest in the dual-use group. This pattern highlights the nonadditive and potentially interaction-dependent nature of alcohol and nicotine vaping effects on cardiovascular protein expression patterns that may contribute to a distinct functional phenotype. Full article