Search Results (4,152)

Background: Varicella remains a prevalent vaccine-preventable disease, but breakthrough infections are increasingly reported. However, long-term, population-based studies investigating the temporal and demographic characteristics of breakthrough varicella remain limited. Methods: This retrospective study analyzed surveillance data from Jinhua City, China, from 2016 to 2024. Varicella case records were obtained from the China Information System for Disease Control and Prevention (CISDCP), while vaccination data were retrieved from the Zhejiang Provincial Immunization Program Information System (ISIS). Breakthrough cases were defined as infections occurring more than 42 days after administration of the varicella vaccine. Differences in breakthrough interval were analyzed across subgroups defined by dose, sex, age, population category, and vaccination type. A bivariate cubic regression model was used to assess the combined effect of initial vaccination age and dose interval on the breakthrough interval. Results: Among 28,778 reported varicella cases, 7373 (25.62%) were classified as breakthrough infections, with a significant upward trend over the 9-year period (p < 0.001). Most cases occurred in school-aged children, especially those aged 6–15 years. One-dose recipients consistently showed shorter breakthrough intervals than two-dose recipients (M = 62.10 vs. 120.10 months, p < 0.001). Breakthrough intervals also differed significantly by sex, age group, population category, and vaccination type (p < 0.05). Regression analysis revealed a negative correlation between the initial vaccination age, the dose interval, and the breakthrough interval (R² = 0.964, p < 0.001), with earlier and closely spaced vaccinations associated with longer protection. Conclusions: The present study demonstrates that a two-dose varicella vaccination schedule, when initiated at an earlier age and administered with a shorter interval between doses, provides more robust and longer-lasting protection. These results offer strong support for incorporating varicella vaccination into China’s National Immunization Program to enhance vaccine coverage and reduce the public health burden associated with breakthrough infections. Full article

Schizophrenia (SCZ) is a complex psychiatric disorder with heterogeneous molecular underpinnings that remain poorly resolved by conventional single-omics approaches, limiting biomarker discovery and mechanistic insights. To address this gap, we applied an artificial intelligence (AI)-driven multi-omics framework to an open access dataset comprising plasma proteomics, post-translational modifications (PTMs), and metabolomics to systematically dissect SCZ pathophysiology. In a cohort of 104 individuals, comparative analysis of 17 machine learning models revealed that multi-omics integration significantly enhanced classification performance, reaching a maximum AUC of 0.9727 (95% CI: 0.8889–1.000) using LightGBMXT, compared to 0.9636 (95% CI: 0.8636–1.0000) with CNNBiLSTM for proteomics alone. Interpretable feature prioritization identified carbamylation at immunoglobulin-constant region sites IGKC_K20 and IGHG1_K8, alongside oxidation of coagulation factor F10 at residue M8, as key discriminative molecular events. Functional analyses identified significantly enriched pathways including complement activation, platelet signaling, and gut microbiota-associated metabolism. Protein interaction networks further implicated coagulation factors F2, F10, and PLG, as well as complement regulators CFI and C9, as central molecular hubs. The clustering of these molecules highlights a potential axis linking immune activation, blood coagulation, and tissue homeostasis, biological domains increasingly recognized in psychiatric disorders. These results implicate immune–thrombotic dysregulation as a critical component of SCZ pathology, with PTMs of immune proteins serving as quantifiable disease indicators. Our work delineates a robust computational strategy for multi-omics integration into psychiatric research, offering biomarker candidates that warrant further validation for diagnostic and therapeutic applications. Full article

Mechanical friction offers a frequent approach for sustainable energy harvesting, as it can be captured and transformed into electricity by means of the triboelectric phenomenon. Theoretically, this electricity may subsequently be employed to drive electrochemical water purification processes. Herein, the experimental results confirm that the SiC particles effectively trigger the tribocatalytic decomposition of Rhodamine B (RhB). During the tribocatalytic decomposition of dye, mechanical friction is generated at the contact surface between the tribocatalyst and a custom-fabricated polytetrafluoroethylene (PTFE) rotating disk, under varying conditions of stirring speed, temperature, and pH value. Hydroxyl radicals and superoxide radicals are confirmed as the dominant reactive species participating in tribocatalytic dye decomposition, as demonstrated by reactive species inhibition experiments. Furthermore, the SiC particles demonstrate remarkable reusability, even after being subjected to five consecutive recycling processes. The exceptional tribocatalytic performance of SiC particles makes them potentially applicable in water purification by harnessing environmental friction energy. Full article

Background/Objective: Staphylococcus aureus (S. aureus) is a clinically significant pathogenic bacterium. Daptomycin (DAP) is a cyclic lipopeptide antibiotic used to treat infections caused by multidrug-resistant Gram-positive bacteria, including S. aureus. However, DAP currently faces clinical limitations due to its short half-life, toxic side effects, and increasingly severe drug resistance issues. This study aimed to develop a biomimetic nano-drug delivery system to enhance targeting ability, prolong blood circulation, and mitigate resistance of DAP. Methods: DAP-loaded chitosan nanocomposite particles (DAP-CS) were prepared by electrostatic self-assembly. Macrophage membrane vesicles (MM) were prepared by fusion of M1-type macrophage membranes with 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC). A biomimetic nano-drug delivery system (DAP-CS@MM) was constructed by the coextrusion process of DAP-CS and MM. Key physicochemical parameters, including particle diameter, zeta potential, encapsulation efficiency, and membrane protein retention, were systematically characterized. In vitro immune escape studies and in vivo zebrafish infection models were employed to assess the ability of immune escape and antibacterial performance, respectively. Results: The particle size of DAP-CS@MM was 110.9 ± 13.72 nm, with zeta potential +11.90 ± 1.90 mV, and encapsulation efficiency 70.43 ± 1.29%. DAP-CS@MM retained macrophage membrane proteins, including functional TLR2 receptors. In vitro immune escape assays, DAP-CS@MM demonstrated significantly enhanced immune escape compared with DAP-CS (p < 0.05). In the zebrafish infection model, DAP-CS@MM showed superior antibacterial efficacy over both DAP and DAP-CS (p < 0.05). Conclusions: The DAP-CS@MM biomimetic nano-drug delivery system exhibits excellent immune evasion and antibacterial performance, offering a novel strategy to overcome the clinical limitations of DAP. Full article

In the field of interferometric fiber-optic sensing, the phase-shifting technique is well known as a highly efficient method for retrieving the phase signal from the interference light intensity. The rectangular-pulse binary phase modulation (RPBPM) method is a typical phase-shifting method with the advantages of high efficiency, low complexity, and easy array multiplexing. Exploring the impact of the parameters on the performance is of great significance for guiding its application in practical systems. In this study, the influence of the sampling interval and modulation depth deviation involved in the method is analyzed in detail. Through a comparative simulation analysis with the traditional heterodyne and phase-generated carrier methods, the superiority of the RPBPM method is effectively validated. Meanwhile, an improved method based on the ellipse fitting of the Lissajous figure is proposed to compensate for the error and improve the signal-to-noise-and-distortion ratio (SINAD) from 26.3 dB to 37.1 dB in a specific experiment. Finally, the experimental results guided by the above method show excellent performance in a practical vibration system. Full article

The evaporation dynamics of droplets on smooth and inclined micro-pillar surfaces were experimentally investigated. The surface temperature was increased from 50 °C to 120 °C, with the inclination angles being 0°, 30°, 45°, and 60° respectively. The dynamic parameters, including contact area, nucleation density, bubble stable diameter, and droplet asymmetry, were recorded using two high-speed video cameras, and the corresponding evaporation performance was analyzed. Experimental results showed that the inclination angle had a significant influence on the evaporation of micro-pillar surfaces than smooth surfaces as well as a positive correlation between the enhancement performance of the micro-pillars and increasing inclination angles. This angular dependence arises from surface inclination-induced tail elongation and the corresponding asymmetry of droplets. With definition of the one-dimensional asymmetry factor (ε) and volume asymmetry factor (γ), it was proven that although the asymmetric thickness of the droplets reduces the nucleation density and bubble stable diameter, the droplet asymmetry significantly increased the heat exchange area, resulting in a 37% improvement in the evaporation rate of micro-pillar surfaces and about a 15% increase in its enhancement performance to smooth surfaces when the inclination angle increased from 0°to 60°. These results indicate that asymmetry causes changes in heat transfer conditions, specifically, a significant increase in the wetted area and deformation of the liquid film, which are the direct enhancement mechanisms of inclined micro-pillar surfaces. Full article

Microplastics (MPs) can affect fish health by inducing oxidative stress, but their impact on structural coloration remains poorly understood. This study investigated the effects of environmentally relevant concentrations (16 and 160 μg/L) of MPs and nanoplastics (NPs) exposure on growth, oxidative stress and structural coloration in blue strain guppy fish (Poecilia reticulata). Results showed exposure to 160 μg/L MPs significantly reduced specific growth rate of fish compared to controls. Plastic accumulation followed a dose-dependent pattern, especially within gut concentrations. Oxidative stress responses differed between MPs and NPs: 160 μg/L MPs decreased SOD activity in skin and reduced GSH levels, while 160 μg/L NPs increased MDA levels in gut tissues, indicating severe lipid peroxidation. Structural coloration analysis revealed exposure to 160 μg/L MPs decreased lightness and increased yellowness, demonstrating reduced blue coloration. This was accompanied by an increase in skin uric acid content, suggesting that guanine conversion might occur to combat oxidative stress. These findings demonstrate that MPs, particularly at high concentrations, impair growth and induce oxidative stress in guppies. To counteract stress, guanine in iridophores may be converted into uric acid, leading to a decline in structural coloration. This study is the first to reveal that MPs disrupt structural coloration of fish, providing new insights into the ecological risks of plastic pollution on aquatic organisms. Full article

Soil salinization in oasis areas of arid regions is recognized as a dynamic and multifaceted environmental threat influenced by both natural processes and human activities. In this study, 13 spatiotemporal predictors derived from field surveys and remote sensing are utilized to construct a spatial probabilistic model of salinization. A Bayesian Belief Network is integrated with spline interpolation in ArcGIS to map the likelihood of salinization, while Partial Least Squares Structural Equation Modeling (PLS-SEM) is applied to analyze the interactions among multiple drivers. The test results of this model indicate that its average sensitivity exceeds 80%, confirming its robustness. Salinization risk is categorized into degradation (35–79% probability), stability (0–58%), and improvement (0–48%) classes. Notably, 58.27% of the 1836.28 km² Keriya Oasis is found to have a 50–79% chance of degradation, whereas only 1.41% (25.91 km²) exceeds a 50% probability of remaining stable, and improvement probabilities are never observed to surpass 50%. Slope gradient and soil organic matter are identified by PLS-SEM as the strongest positive drivers of degradation, while higher population density and coarser soil textures are found to counteract this process. Spatially explicit probability maps are generated to provide critical spatiotemporal insights for sustainable oasis management, revealing the complex controls and limited recovery potential of soil salinization. Full article

Background/Objectives: Prior research suggest that poor working memory significantly contributes to the growth of overweight and obesity. This study investigated the behavioral and neural aspects of general and food-specific working memory in females with overweight or obesity (OW/OB). Method: A total of 54 female participants, with 26 in the OW/OB group and 28 in the normal-weight (NW) group, completed a general and a food-related two-back task while an EEG was recorded. Results: In the general task, the OW/OB group showed significantly poorer performance (higher IES) than the NW group (p = 0.018, η² = 0.10), with reduced theta power during non-target trials (p = 0.040, η² = 0.08). No group differences were found for P2, N2, or P3 amplitudes. In the food-related task, significant group × stimulus interactions were observed. The OW/OB group showed significantly higher P2 amplitudes in high-calorie (HC) versus low-calorie (LC) food conditions (p = 0.005, η² = 0.15). LPC amplitudes were greater in the OW/OB group for HC targets (p = 0.036, η² = 0.09). Alpha power was significantly lower in OW/OB compared to NW in HC non-targets (p = 0.030, η² = 0.09), suggesting a greater cognitive effort. Conclusions: These findings indicate that individuals with OW/OB exhibit deficits in general working memory and heightened neural responses to high-calorie food cues, particularly during non-target inhibition. The results suggest an interaction between reward salience and cognitive control mechanisms in obesity. Full article

The present study analyzes individual differences in the facilitative processing of grammatical gender by heritage speakers of Spanish, asking whether these differences correlate with lexical proficiency. Results from an eye-tracking study in the Visual World Paradigm replicate prior findings that, as a group, heritage speakers of Spanish show facilitative processing of gender. Importantly, in a follow-up within-group analysis, we test whether three measures of lexical proficiency—oral picture-naming, verbal fluency, and LexTALE—predict individual performance. We find that lexical proficiency, as measured by LexTALE, predicts overall word recognition; however, we observe no effects of the other measures and no evidence that lexical proficiency modulates the strength of the facilitative effect. Our results highlight the importance of carefully selecting tools for proficiency assessment in experimental studies involving heritage speakers, underscoring that the absence of evidence for an effect of proficiency based on a single measure should not be taken as evidence of absence. Full article

Low Earth orbit (LEO) signal of opportunity (SOP) positioning relies on the accumulation of epochs obtained through prolonged observation periods. The contribution of an LEO satellite single epoch to positioning accuracy is influenced by multi-level characteristics that are challenging for traditional models. To address this limitation, we propose an Agent-Weighted Recursive Least Squares (RLS) Positioning Framework (AWR-PF). This framework employs an agent to comprehensively analyze individual epoch characteristics, assess their credibility, and convert them into adaptive weights for RLS iterations. We developed a novel Markov Decision Process (MDP) model to assist the agent in addressing the epoch weighting problem and trained the agent utilizing the Double Deep Q-Network (DDQN) algorithm on 107 h of Iridium signal data. Experimental validation on a separate 28 h Iridium signal test set through 97 positioning trials demonstrated that AWR-PF achieves superior average positioning accuracy compared to both standard RLS and randomly weighted RLS throughout nearly the entire iterative process. In a single positioning trial, AWR-PF improves positioning accuracy by up to 45.15% over standard RLS. To the best of our knowledge, this work represents the first instance where an AI algorithm is used as the core decision-maker in LEO SOP positioning, establishing a groundbreaking paradigm for future research. Full article

Members of the heat shock protein 20 (HSP20) family of proteins play an important role in responding to various forms of stress. Here, the expression of ClaHSP17.4 was induced by heat stress in watermelon. Then, a floral dipping approach was used to introduce the pCAMBIA1391b-GFP overexpression vector encoding the heat tolerance-related gene ClaHSP17.4 from watermelon into Arabidopsis thaliana, and we obtained ClaHSP17.4-overexpressing Arabidopsis plants. Under normal conditions, the phenotypes of transgenic and wild-type (WT) Arabidopsis plants were largely similar. Following exposure to heat stress, however, the germination rates (96%) of transgenic Arabidopsis plants at the germination stages were significantly higher than those of wild-type idopsis (17%). Specifically, the malondialdehyde (MDA) content of transgenic Arabidopsis was half that of the control group, while the activities of peroxidase (POD) and superoxide dismutase (SOD) were 1.25 times those of the control group after exposure to high temperatures for 12 h at the seedling stages. The proline content in ClaHSP17.4-overexpressing transgenic Arabidopsis increased by 17% compared to WT plants (* p < 0.05), while the soluble sugar content rose by 37% (* p < 0.05). These results suggest that ClaHSP17.4 overexpression indirectly improves the antioxidant capacity and osmotic regulatory capacity of Arabidopsis seedlings, leading to improved survival and greater heat tolerance. Meanwhile, the results of this study provide a reference for further research on the function of the ClHSP17.4 gene and lay a foundation for breeding heat-tolerant watermelon varieties and advancing our understanding of plant adaptation to environmental stress. Full article

Accurate and robust spatial perception is fundamental for dynamic 3D city modeling and urban environmental sensing. High-resolution remote sensing data, particularly LiDAR point clouds, are pivotal for these tasks due to their lighting invariance and precise geometric information. However, processing and aligning sequential LiDAR point clouds in complex urban environments presents significant challenges: traditional point-based or feature-matching methods are often sensitive to urban dynamics (e.g., moving vehicles and pedestrians) and struggle to establish reliable correspondences. While deep learning offers solutions, current approaches for point cloud alignment exhibit key limitations: self-supervised losses often neglect inherent alignment uncertainties, and supervised methods require costly pixel-level correspondence annotations. To address these challenges, we propose UnMinkLO-Net, an end-to-end self-supervised LiDAR odometry framework. Our method is as follows: (1) we efficiently encode 3D point cloud structures using voxel-based sparse convolution, and (2) we model inherent alignment uncertainty via covariance matrices, enabling novel self-supervised loss based on uncertainty modeling. Extensive evaluations on the KITTI urban dataset demonstrate UnMinkLO-Net’s effectiveness in achieving highly accurate point cloud registration. Our self-supervised approach, eliminating the need for manual annotations, provides a powerful foundation for processing and analyzing LiDAR data within multi-sensor urban sensing frameworks. Full article

This study explores the determinants of startup intention within the context of e-commerce platform-based startups in South Korea. We employ an extended technology acceptance model (TAM) that integrates individual, social, and entrepreneurial characteristics. A two-step analytical approach is applied, combining variable extraction through data mining and hypothesis testing using structural equation modeling. The results indicate that personal and social factors—such as entrepreneurial mindset and social influence—positively affect perceived usefulness, while job relevance and exposure to successful startup models enhance perceived ease of use. In contrast, security concerns and technological barriers negatively impact these relationships, posing critical obstacles to platform-based startups. This study extends the TAM framework to the platform-based startup context, offering theoretical contributions and proposing policy implications, including promoting digital literacy, developing entrepreneurial networks, and addressing security and regulatory issues. These insights offer a deeper understanding of how platform environments shape entrepreneurial behavior, providing practical guidance for startup founders, developers, and policymakers. Full article

Fecal microbiota transplantation (FMT) promotes growth performance and intestinal development in yellow-feathered broilers, but whether the virome and metabolites contribute to its growth-promoting effect remains unclear. This study removed the microbiota from FMT filtrate using a 0.45 μm filter membrane, retaining the virome and metabolites to perform fecal virome transplantation (FVT), aiming to investigate its regulatory role in broiler growth. Healthy yellow-feathered broilers with high body weights (top 10% of the population) were used as FVT donors. Ninety-six 8-day-old healthy male yellow-feathered broilers (95.67 ± 3.31 g) served as FVT recipients. Recipient chickens were randomly assigned to a control group and an FVT group. The control group was gavaged with 0.5 mL of normal saline daily, while the FVT group was gavaged with 0.5 mL of FVT solution daily. Growth performance, immune and antioxidant capacity, intestinal development and related gene expression, and microbial diversity were measured. The results showed that FVT improved the feed utilization rate of broilers (the feed conversion ratio decreased by 3%; p < 0.05), significantly increased jejunal length (21%), villus height (69%), and crypt depth (84%) (p < 0.05), and regulated the jejunal barrier: insulin-like growth factor-1 (IGF-1) (2.5 times) and Mucin 2 (MUC2) (63 times) were significantly upregulated (p < 0.05). FVT increased the abundance of beneficial bacteria Lactobacillales. However, negative effects were also observed: Immunoglobulin A (IgA), Immunoglobulin G (IgG), Immunoglobulin M (IgM), Interleukin-1 beta (IL-1β), Interleukin-6 (IL-6), Tumor Necrosis Factor-alpha (TNF-α), and Interferon-gamma (IFN-γ) in broilers were significantly upregulated (p < 0.05), indicating immune system overactivation. Duodenal barrier-related genes Mucin 2 (MUC2), Occludin (OCLN), Claudin (CLDN1), and metabolism-related genes solute carrier family 5 member 1 (SLC5A1) and solute carrier family 7 member 9 (SLC7A9) were significantly downregulated (p < 0.05). The results of this trial demonstrate that, besides the microbiota, the gut virome and metabolites are also functional components contributing to the growth-promoting effect of FMT. The differential responses in the duodenum and jejunum reveal spatial heterogeneity and dual effects of FVT on the intestine. The negative effects limit the application of FMT/FVT. Identifying the primary functional components of FMT/FVT to develop safe and targeted microbial preparations is one potential solution. Full article