Search Results (2,864)

Marine red algae have been reported to contain a variety of bioactive compounds that are effective in promoting wound-healing processes. In the present study, the wound-healing potential of Grateloupia angusta, which has been rarely explored, was examined using in vitro and in vivo models. A 70% ethanol extract of G. angusta (GAE) was prepared and profiled by liquid chromatography–mass spectrometry (LC-MS). Its effects on the wound-healing process were examined using three different types of cells that participate in this process, namely, Raw264.7, human umbilical vein endothelial cells (HUVECs), and human dermal fibroblasts (HDFs). Various assays including migration/scratch, tube formation, procollagen type I C-peptide production, and Western blotting were used to investigate the therapeutic potential of GAE. In vivo efficacy was tested in a mouse full-thickness skin incision wound model. In HUVECs, GAE increased viability, migration, tube formation, and vascular endothelial growth factor (VEGF) expression. Raw264.7 cells also showed increased VEGF production following GAE treatment. In HDFs, GAE did not affect proliferation and migration, but did increase collagen production. In mice, GAE accelerated wound closure from day 3 to day 5 and increased granulation/matrix with higher proliferating cell nuclear antigen (PCNA) and cluster of differentiation 31 (CD31) expression after a single topical application. In addition, keratin 14 (K14) expression was restored in GAE-treated wound tissues, suggesting improved epidermal re-epithelialization. Taken together, GAE promotes matrix production and pro-angiogenic activity in vitro and improves early wound repair in vivo, suggesting that G. angusta is a promising marine-derived candidate for wound-healing adjuvants. The results of the present study support further bioassay-guided fractionation and mechanistic validation in future studies. Full article

In complex sedimentary environments, the identification of thin sandbodies and the accurate prediction of their thickness remain challenging, particularly when relying on a single analytical approach. Taking the lower sub-member of the fourth member of the Shahejie Formation (Es₄^L) in the Chenguanzhuang area of the Dongying Depression as a case study, this study proposes a quantitative prediction method that integrates sedimentary facies constraints with machine learning-based seismic multi-attribute fusion. Based on core observations, well log data, and 3D seismic datasets, the study area is subdivided into two zones: Zone I (shallow-water delta front) and Zone II (shore–shallow lake). Sensitive attributes for each zone are optimized using Pearson correlation analysis and hierarchical clustering, and five machine learning models—SVR, Random Forest, MLP, Ridge Regression, and Lasso Regression—are systematically evaluated. The MLP model is selected for Zone I, achieving R² values of 0.856 and 0.936 for the training and test sets, respectively, whereas Ridge Regression combined with leave-one-out cross-validation (LOOCV) is adopted for Zone II to mitigate overfitting caused by limited well data, yielding R² values of 0.864 and 0.779. Compared with conventional linear regression (R² = 0.45), the proposed approach significantly improves the accuracy of quantitative sandbody prediction, providing a reliable geological basis for hydrocarbon exploration and an effective technical framework for similar complex sedimentary environments. Full article

Nitridation of different materials using ion implantation is of considerable interest for many applications. As electronic components, oxynitride (SiO_xN_y) layers exhibit beneficial properties such as precise compositional variability, refractive index tunability, oxidation resistance, and low mechanical stress. In the present study we investigate nanoscale SiO_xN_y synthesized using ion implantation methods. To introduce N⁺ ions into a shallow Si subsurface region, both conventional ion beam implantation and plasma immersion ion implantation with subsequent high-temperature treatment in dry O₂ are used. The optical and morphological properties and chemical bonding of formed SiO_xN_y layers were studied by applying spectroscopic ellipsometry in the range of VIS-Near IR (SE) and IR (IR-SE), Raman spectroscopy and Atomic Force Microscopy (AFM). Monte Carlo modeling of implant profiles contributed to understanding physical and chemical processes and predicted different influences of the incorporated N⁺ ions on the oxidation mechanism, confirmed by the thickness dependence of SiO_xN_y/Si layers obtained from the SE data analysis. IR-SE spectral analysis established the formation of Si-O, Si-N, Si-N-O and Si-Si chemical bonds in the grown layers. The occurrence of amorphization of the Si crystal lattice due to incorporation of high-energy N⁺ ions into the Si lattice is confirmed by the Raman and ellipsometry results. The free Si atoms can congregate, forming nanocrystalline clusters. AFM imaging revealed that both implantation methods left the surface of the resulting SiO_xN_y layers considerably smooth with similar roughness parameter values. The results of the studies imply that the technological approaches used allow the production of high-quality nanoscale silicon oxynitride films with appropriate tunable composition and properties for possible application in advanced electronic devices for nanoelectronics, optoelectronics and sensor applications. Full article

Glucosamine (GlcN) is an essential amino monosaccharide widely used in pharmaceuticals, nutraceuticals, and cosmetics. Microbial fermentation presents a sustainable alternative to its traditional chemical production. However, in Saccharomyces cerevisiae, competitive carbon flux towards ethanol significantly limits GlcN yields. In this study, an S. cerevisiae strain for GlcN biosynthesis was engineered by integrating heterologous GlmD (glucosamine-6-phosphate deaminase) and GlmP (glucosamine-6-phosphate phosphatase) genes. To redirect carbon flux, the pyruvate decarboxylase genes pdc1, pdc5, and pdc6 were sequentially knocked out using the Clustered Regularly Interspaced Short Palindromic Repeats Cas9 (CRISPR-Cas9) approach, generating strains S. cerevisiaeGlmDP/pdc1Δ, GlmDP/pdc1Δpdc5Δ, and GlmDP/pdc1Δpdc5Δpdc6Δ. S. cerevisiae GlmDP/pdc1Δpdc5Δpdc6Δ achieved a GlcN titer of 2.20 ± 0.11 g/L, a 1.54-fold increase over the parental S. cerevisia GlmDP strain, while its ethanol yield decreased by 26%. This enhancement was achieved without significantly affecting cell growth or glucose consumption. Comparative transcriptomics between the triple-knockout and parental yeasts revealed 892 differentially expressed genes. Pathways related to glycolysis and ethanol formation were predominantly downregulated, whereas pathways potentially supporting GlcN synthesis were upregulated. The engineered strain demonstrated high genetic stability over 50 generations. Our findings demonstrate that disrupting ethanol formation is an effective strategy to enhance GlcN production in S. cerevisiae, providing valuable insights for carbon flux redistribution. Full article

Symmetry and structural balance play a fundamental role in the collective behavior of networked agent systems (NASs). In particular, cluster formation tracking, representing the emergence and maintenance of symmetric group structures, has attracted significant attention due to its wide applications in robotics and autonomous systems. However, most existing approaches assume autonomous leaders, which may not be applicable in scenarios where human intervention is required. With this in mind, this paper addresses the cluster formation tracking problem for NASs with collision avoidance, where the leader receives control inputs from a human-in-the-loop (HiTL), making the leader a non-autonomous system. A distributed control protocol is developed so that followers can track the trajectories of their designated leaders using only relative information from neighboring agents. Sufficient conditions are established to guarantee collision-free cluster formation tracking, and Lyapunov-based analysis is employed to prove the asymptotic convergence of the subgroup tracking errors. In the proposed framework, human intervention is incorporated through external commands applied to the leaders, which makes the leader dynamics non-autonomous while preserving the distributed nature of the follower controllers. Simulation studies on a 13-agent network with three subgroups show that all followers achieve the desired time-varying cluster formations under HiTL-driven leader motions, with convergence times ranging from 4.21 s to 5.12 s. Moreover, the final tracking errors of all followers are reduced below $9.07\times {10}^{-5}$, while the minimum pairwise distances within each subgroup remain strictly above the prescribed safety threshold. These quantitative results verify both the effectiveness of the proposed protocol and the practical feasibility of integrating HiTL commands into collision-free cluster formation tracking. Full article

Plastic pollution from packaging waste is driving the development of biodegradable composites for sustainable packaging. In this work, poly(butylene adipate-co-terephthalate)/poly(3-hydroxybutyrate) (PBAT/PHBH) blends (50/50 wt.%) were reinforced with agro-industrial waste fillers—spent coffee grounds (SCG), brewer’s spent grain (BSG), and cellulose powder (CP)—at 1–15 wt.% loading. The effects of these fillers on tensile properties, impact strength, and thermal stability were examined and supported by scanning electron microscopy (SEM) of fracture surfaces and thermogravimetric analysis (TGA). The neat PBAT/PHBH blend exhibited balanced stiffness and ductility. Low BSG loadings (≤5 wt.%) produced the greatest toughening, with impact strength increasing by ~92% and elongation at break significantly improving over the neat blend. SEM analysis indicated crack deflection and particle pull-out as dominant energy-dissipation mechanisms at low BSG loading. At higher BSG loading (15 wt.%), particle clustering and larger voids acted as stress concentrators, reducing impact performance. SCG improved ductility at low loading (1 wt.%), whereas increasing SCG content led to progressive reductions in tensile strength and elongation due to increased debonding and microvoid formation. In contrast, CP exhibited minimal reinforcement efficiency within the investigated range (1–5 wt.%). Overall, filler addition generally reduced tensile strength and, in several cases, tensile modulus, reflecting limited interfacial compatibility between the hydrophilic lignocellulosic fillers and the hydrophobic polyester matrix. TGA indicated a modest improvement in thermal stability at higher BSG loadings, reflected by shifts in T_5% and T_max1 (PHBH) toward higher temperatures. Overall, this study demonstrates that upcycled coffee and beer waste fillers can impart specific toughness benefits to biodegradable PBAT/PHBH blends, but interfacial incompatibility currently limits their reinforcement efficiency. The findings highlight the potential and challenges of these biocomposites for sustainable packaging applications and suggest that interface engineering (e.g., compatibilizers) will be key to unlocking optimal performance. Full article

This work investigated the membrane fouling mechanisms during the microfiltration of oat protein–β-glucan complexes. Microfiltration experiments were conducted under various pH conditions, protein-to-polysaccharide ratios, and ionic strengths. The fouling behavior was analyzed using multiple membrane fouling models to systematically elucidate the relationships among the particle characteristics, rheological behaviors, and membrane fouling. When the pH was adjusted to 7.8, the multimodal particle size distribution of the complexes promoted the formation of a loosely structured cake layer on the membrane surface, accompanied by partial obstruction of membrane pore entrances. On the contrary, the complexes, shown as having a monomodal particle size distribution and similar particle size to the membrane pore, formed compact cake layers and strong membrane fouling resistance. At pH 4.8, protein hydrophobic aggregation generated large particulate clusters that formed a loose cake layer during microfiltration, resulting in a decrease in membrane fouling resistance. Increasing the β-glucan content reduced membrane resistance through enhancing steric hindrance and hydrophilicity. This research provides a theoretical foundation for optimizing membrane separation process parameters in the production of diversified oat-based products. Full article

Low-temperature stress during the jointing stage severely disrupts the coordination of the source–flow–sink system in winter wheat. To elucidate the underlying mechanism, three wheat cultivars with different winter habits (Zhenmai 12, Jimai 22, and Shannong 38) were selected and subjected to six temperature levels (−6 °C to 8 °C) and three stress durations (2–6 days). The effects of vascular bundle traits on the transport of photosynthetic products, dry matter distribution, and yield formation were analyzed. The results showed that Zhenmai 12 and Jimai 22 completely ceased photosynthesis under 0 °C and −3 °C, respectively. The leaf vascular bundle area continuously decreased with increasing low-temperature stress, while the proportion of xylem and phloem initially increased by approximately 15% and 10%, respectively, before rapidly decreasing to 65% of the control value. In the stem, the three vascular bundle parameters initially increased by 20%, 25%, and 20%, respectively, before quickly decreasing to 50%. Changes in the vascular bundle structure weakened the transport capacity of assimilates, with dry matter in leaves and stems decreasing by 15–20% and 10%, respectively, while the root dry matter increased by 20–30%. Correlation analysis revealed highly significant relationships (p < 0.001) between vascular bundle parameters and yield components. Principal component and cluster analyses indicate that the area of leaf and stem vascular bundles, maximum net photosynthetic rate, and water use efficiency may be key indicators in explaining the variation in yield. Radar plots further validated this finding, showing that Zhenmai 12 and Jimai 22 are more sensitive to changes in the maximum net photosynthetic rate, while Shannong 38 exhibits a greater sensitivity to changes in water use efficiency. Based on existing research on photosynthetic pathways and dry matter distribution, this study innovatively investigates the potential relationship between material transport and yield formation under low-temperature stress during the jointing stage from the perspective of anatomical structure and functional coupling. The findings provide new insights into understanding the structural impact of low-temperature stress on crop yield formation and offer theoretical support for identifying the structural basis of limited material transport under stress and for developing disaster diagnostic models driven by structural parameters. Full article

Membrane curvature is a fundamental biophysical property of cellular membranes that underlies essential processes such as vesicle formation, organelle shaping, intracellular trafficking, and membrane scission. While traditionally studied in the context of cell biology and membrane dynamics, membrane curvature is now emerging as a critical, albeit underrecognized, regulator of oncogenic transformation and tumor progression. Curvature not only governs the mechanical properties of the membrane but also influences the spatial localization and activation of key signaling proteins, including Ras family GTPases, whose oncogenic functions are closely dependent on membrane topology. Cancer is frequently associated with disruptions in the regulation of membrane curvature as a result of aberrant lipid metabolism, overexpression of curvature-modulating proteins, and cytoskeletal remodeling. These changes facilitate the hallmarks of malignancy such as uncontrolled proliferation, enhanced motility, immune evasion, metabolic rewiring, and therapy resistance. Notably, recent evidence reveals that curvature acts as a spatial cue for Ras activation, particularly during epithelial-to-mesenchymal transition (EMT), where curvature-driven Ras relocalization amplifies growth factor signaling and promotes metastasis. This review provides a comprehensive overview of the molecular determinants that generate and sense membrane curvature from lipid shape and membrane asymmetry, BAR domain proteins, and actin dynamics, and explores how these mechanisms are hijacked in cancer. We describe the feedback between membrane architecture and oncogenic pathways such as Ras/MAPK and PI3K/AKT, emphasizing the role of curvature in shaping signal transduction platforms. It should be noted that “curvature-driven signaling” is defined as signaling regulation that arises from membrane-geometry-dependent localization, clustering, or activation of signaling proteins, while “curvature-sensitive platforms” refer to membrane subdomains whose specific curvature selectively recruits and stabilizes signaling complexes. Furthermore, we examine how these biophysical alterations impact vesicular trafficking, organelle morphology, and secretion, all of which are co-opted to support tumor development. From a translational standpoint, we assess emerging therapeutic strategies designed to target curvature-regulating factors and leverage membrane topology for precision drug delivery. Innovations in nanomedicine, super-resolution imaging, and curvature-sensing biosensors are also discussed as tools for both diagnostics and therapeutic monitoring. By integrating advances in membrane biophysics, cancer signaling, and bioengineering, this review highlights membrane curvature as a central and actionable dimension of cancer biology. Full article

This study presents experimental evidence of random magnetic behavior in modified barium hexaferrites. We demonstrate a significant shift in the magnetic properties of these materials upon the incorporation of divalent cations (Ni²⁺, Cu²⁺, Mn²⁺), which produces the formation of ceramic nanocomposites. X-ray diffraction, scanning electron microscopy, and laser diffraction reveal that these systems comprise micron-sized clusters formed by sintering polycrystalline nanoparticles. The cation incorporation occurs randomly across each sample, creating conditions conducive to random anisotropy magnetism. We confirm this behavior in our samples by fitting the magnetization data near saturation to a corresponding theoretical model. Additionally, we investigate the microwave absorption capabilities of these systems in the GHz range by calculating the reflection loss coefficient of mm-thick samples using transmission-line theory. The results predict broad (up to 2 GHz) and high (around 60 dB on average) absorption signals. In the case of the thinnest samples (1–2 mm), the Cu-substituted system presents broader absorption bandwidths than the pure hexaferrite and, therefore, proves to be more efficient for stealth applications in lightweight sectors. These findings suggest ceramic nanocomposites are promising candidates for random anisotropy magnets, highlighting their potential as efficient microwave absorbers, consistent with recent theoretical predictions. Full article

Recent years have witnessed growing interest in CO₂ and in the possibility of injecting it into the Earth’s crust for multiple purposes. In addition to the fact that pure CO₂ is already present in some geological formations, the most debated is Carbon Capture and Storage (CCS), which aims to capture and trap CO₂ through water-assisted reactions that promote its precipitation; moreover, proposed technological improvements to geothermal plants foresee the use of pure CO₂ as a working fluid and energy carrier for electricity generation in terms of MWh. These applications require detailed knowledge and a deep understanding of CO₂ behaviour under non-standard conditions. Upon entering the Earth’s crust, CO₂ is subjected to progressively increasing temperature and pressure. The resulting effects are not limited to a reduction in intermolecular distance; they also include changes in molecular geometry, as well as in chemical and thermodynamic behaviour. For instance, a dipole moment may arise even in the gaseous phase as intermolecular distances decrease. Moreover, CO₂ typically reaches supercritical conditions at depths of approximately 700 m. It is therefore necessary to account for both phase transitions and variations in molecular structure, as these can significantly influence the surrounding environment and the stoichiometric relationships with other substances. In this work, a steady-state column was simulated, representing CO₂ injection down to a depth of 5 km, assuming an average geothermal gradient of 30 °C/km and nine different initial pressures, so nine different steady state columns. The results highlight the presence of a wedge-shaped region acting as a barrier for stepwise-equilibrated CO₂: the computed CO₂ column profiles avoid this region. This wedge includes part of the liquid–gas boundary under subcritical conditions, as well as the Widom lines above the critical point. It effectively separates two supercritical regimes, namely gas-like and liquid-like domains. In this context, the present work provides insights into the Widom region—possibly extending into subcritical conditions—and into these two distinct regimes. This may have implications for the solvent capacity of CO₂ for ionic species. Ultimately, the initial pressure appears to determine the behaviour of CO₂ at depth. Full article

As a world-renowned tourist and gaming city, Macau’s jewelry industry has formed significant spatial clustering driven by the integration of the tourism and gaming industries. However, existing research has not thoroughly explored the coupling mechanism between the agglomeration of this high-value industry and tourism potential circulation characteristics. Meanwhile, the industry confronts practical challenges, including an unbalanced layout between high-end and local brands, intense competition in core areas, and distinct service coverage blind spots in non-core areas. To fill these research gaps, this study takes the Macau Special Administrative Region as the research scope, integrates POI kernel density estimation, Voronoi diagram analysis, and space syntax to construct a three-dimensional analytical framework encompassing agglomeration intensity, service scope, and tourism flow matching, and systematically investigates the spatial clustering pattern of jewelry stores and its coupling mechanism with tourism potential circulation. The study reveals the following findings: (1) Jewelry stores exhibit a dual-segment, four-core clustering pattern. Among these, 38 high-end brands are concentrated in casino complexes and their surrounding areas, 34 comprehensive brands are evenly distributed across core and residential areas, and 300 local brands are mainly scattered in residential areas of the Macau Peninsula. (2) The service scope of jewelry stores is negatively correlated with agglomeration density. The Voronoi diagram area in core areas is 62% smaller than that in non-core areas, accompanied by a high degree of overlap—35% for high-end brands—and intense competition. In contrast, non-core areas have coverage blind spots accounting for 18% of Macau’s total land area. (3) Under a 300 m walking radius, high-integration paths identified by space syntax demonstrate an 85% matching degree with tourist routes, and the four core areas form differentiated coupling types. This study is the first to quantify the differentiated coupling mechanism between multi-level jewelry brands and tourism potential circulation. It further improves the GIS analysis framework for the coupling between commercial agglomeration and tourist behavior. The revealed negative correlation between service scope and agglomeration density, and the adaptive principle between brand spatial layout and regional functional attributes, provide universal references for similar business formats in tourist cities, including cultural and creative retail and characteristic catering. In practice, this research optimizes the spatial layout of Macau’s jewelry industry and increases the coverage rate of service blind spots to over 85%. It also provides scientific support for tourism route planning and the coordinated development of tourism and commerce in high-density tourist destinations. Full article

Rapid urbanization in the Global South has intensified the formation of mega-urban regions, where conventional urban–rural classifications often fail to capture the complexity of peri-urban systems. In the Jakarta–Bandung Mega-Urban Region (JBMUR), rapid land-use change and socio-economic transformation have produced hybrid landscapes that challenge binary zoning approaches. This study aims to delineate urban, peri-urban, and rural spatial structures using a spatially constrained clustering framework and to evaluate the performance of the Rustiadi Quantitative Zoning Method-2 (RQZM-2) compared with conventional non-spatial clustering (Non-RQZM). Built-environment, accessibility, environmental, and socio-economic indicators derived from remote sensing and spatially disaggregated statistical data were analyzed using grid-based K-Means clustering. Comparative validation using internal metrics, stability analysis, spatial coherence diagnostics, and statistical differentiation tests indicates that RQZM-2 produces more stable, spatially coherent, and interpretable clusters than conventional clustering. The validated four-cluster solution identifies compact urban cores, extensive peri-urban transition belts, and two distinct rural sub-types, revealing a functionally differentiated regional structure across the JBMUR. These findings demonstrate that incorporating spatial contextualization into clustering improves the empirical representation of peri-urban spatial continuity and provides a robust analytical basis for spatial zoning and regional planning in rapidly urbanizing mega-urban regions. Full article

Antimicrobial resistance (AMR) represents a critical global health challenge, with methicillin-resistant Staphylococcus aureus (MRSA) posing a significant threat in both hospital-acquired and community-associated infections. Research has demonstrated that biofilm formation is a key factor contributing to drug resistance in MRSA. In this study, we investigated an fungus, Fusarium oxysporum BPF55, isolated from Blaps rynchopetera, which inhibits MRSA biofilm formation. The aim of this research was to identify the fungal strain and comprehensively characterize its genomic features, as well as to evaluate its anti-MRSA biofilm potential. Whole-genome sequencing revealed a genome size of 50,097,681 base pairs, a GC content of 47.36%, and 16,507 predicted coding genes. AntiSMASH analysis identified 56 secondary metabolite biosynthetic gene clusters, including those involved in the synthesis of various natural products such as terpenes, non-ribosomal peptides, and polyketides. Using UPLC-MS/MS, 15 compounds were annotated from the ethyl acetate extract. Molecular docking studies demonstrated that four compounds exhibit varying affinities for SarA and AgrA, two key proteins involved in MRSA biofilm formation. Overall, these findings suggest that the fungus F. oxysporum BPA55 produces a variety of secondary metabolites and contains bioactive compounds with potential anti-MRSA biofilm activity. Full article

With the increasing penetration of renewable energy in power systems, the effective utilization of pumped storage power plant (PSP) clusters for peak shaving has become an important issue in system operation. In this study, an intraday scheduling model for PSP clusters is formulated to minimize the variance of the system net load, while accounting for operational constraints, including power balance, unit operation, and reservoir energy evolution. The resulting model is a mixed-integer nonlinear programming (MINLP) problem, which is solved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Case studies are conducted on an improved IEEE 39-bus system under both conventional scenarios and extreme renewable energy conditions. The results show that, under a unified peak-shaving objective, PSP clusters exhibit a stable structure of role differentiation even in conventional operating conditions. As the system peak-shaving pressure increases, this differentiation is progressively reinforced along existing functional roles, shifting from renewable energy absorption to peak-period generation support. It tends to converge under high operational stress due to the coupling between load and renewable variability. Further analysis indicates that when capacity differences among PSPs are eliminated, the differentiation structure is significantly weakened, suggesting that physical capability differences constitute an important foundation for the formation of role differentiation. Full article