Search Results (3,244)

 Porcine epidemic diarrhea virus (PEDV) continues to circulate globally, causing substantial economic losses to the swine industry. Historically, PEDV strains are classified into the classical G1, epidemic G2, and S-INDEL genotypes. Among these genotypes, the highly virulent and prevalent G2 genotype has been extensively studied. However, recent clinical outbreaks in China necessitate a reevaluation of the epidemiological and evolutionary dynamics of circulating strains. This study analyzed 37 newly sequenced S genes and public sequences to characterize the genetic variations of S-INDEL strains. Our analysis revealed that S-INDEL strains are endemic throughout China, with a phylogenetic analysis identifying two distinct clades: clade 1, comprising early endemic strains, and clade 2, representing a recently dominant, geographically restricted lineage in China. While inter-genotypic recombination has been documented, our findings also demonstrate that intra-genotypic and intra-clade recombination events contributed significantly to the emergence of clade 2, distinguishing its evolutionary pattern from clade 1. A comparative analysis identified 22 clade-specific amino acid changes, 11 of which occurred in the D0 domain. Notably, mutations at positively selected sites—113 and 114 within the D0 domain, a domain associated with pathogenicity—were specific to clade 2. A phylodynamic analysis indicated Germany as the epicenter of S-INDEL dispersal, with China acting as a sink population characterized by localized transmission networks and frequent recombination events. These results demonstrate that contemporary S-INDEL strains, specifically clade 2, exhibit unique recombination patterns and mutations potentially impacting virulence. Continuous surveillance is essential to assess the pathogenic potential of these evolving recombinant variants and the efficacy of vaccines against them.  Full article

Gut microbiota plays a vital role in host resilience but may be disrupted under environmental antibiotic pressure. The goitered gazelle (Gazella subgutturosa), a keystone ungulate in the Qaidam Basin, is crucial for ecosystem stability. We aimed to investigate how this species responds to antibiotic pressure through gut microbial adaptation. Using 16S rRNA sequencing and weighted gene co-expression network analysis (WGCNA) on fecal and soil samples from six regions, we identified 18 microbial modules, of which three were strongly associated with antibiotics (|r| ≥ 0.75, p < 0.05). Gut microbial α-diversity was lowest in the antibiotic-rich, vegetation-poor TGL region and highest in XRH, where diverse vegetation appeared to buffer antibiotic impact. Antibiotic pressure can reshape gut microbial communities, exerting both adaptive benefits and adverse effects. High-quality habitats may alleviate the negative impacts of antibiotic pressure. Full article

The rainy season characteristics are directly modulated by atmospheric circulation and moisture transport dynamics. Focusing on the characteristics of the rainy season onset date (RSOD), this study aims to advance the understanding and prediction of climate change impacts on agricultural production and disaster mitigation strategies. Based on rainfall data from 66 meteorological stations in northeast China (NEC) from 1961 to 2020, this study determined the patterns of the RSOD in the region and established its mechanistic linkages with atmospheric circulation and water vapor transport mechanisms. This study identifies a climatic regime shift around 2000, with the RSOD transitioning from low to high interannual variability in NEC. Further analysis reveals a strong correlation between the RSOD and atmospheric circulation characteristics: cyclonic vorticity amplifies before the RSOD and dissipates afterward. Innovatively, this study reveals a significant transition in the water vapor transport paths during the early rainy season in NEC around 2000, shifting from eastern Mongolia–Sea of Japan to the northwestern Pacific region. Moreover, the advance or delay of the RSOD directly influences the water vapor transport intensity—an early (delayed) RSOD is associated with enhanced (weakened) water vapor transport. These findings provide a new perspective for predicting the RSOD in the context of climate change while providing critical theoretical underpinnings for optimizing agricultural strategies and enhancing disaster prevention protocols. Full article

Sepsis-induced myocardial injury is age-related and leads to increased mortality. Considering the importance of mitochondrial dysfunction in cardiac impairment, we aimed to investigate whether aging exacerbates the cardiac mitochondrial metabolic response to inflammation, thus leading to increased cardiac dysfunction in the elderly. Cecal ligation and puncture (CLP) was conducted in young adult (12–18 weeks) and aged (19–21 months) male C57BL/6 mice. Cardiac function was detected 20 h post-CLP. Additionally, cardiomyocytes isolated from young adult and aged male mice were used for assessments of mitochondrial respiratory function +/– TNFα or LPS. Protein levels of oxidative phosphorylation (OXPHOS), NADPH oxidase (NOX)2, NOX4, phosphor-STAT3 and STAT3 were determined in mouse hearts 24 h post-CLP and in cardiomyocytes following inflammatory stimuli. CLP significantly reduced cardiac contractility in both young and aged mice, with a higher incidence and greater severity of cardiac functional depression in the older group. Mitochondrial respiratory capacity was decreased in cardiomyocytes derived from aged mice, with increased susceptible to inflammatory toxic effects compared to those from young adult mice. The age-dependent changes were observed in myocardial OXPHOS complexes and NOX4. Importantly, CLP led to a significant increase in OXPHOS protein levels in the hearts of older mice, suggesting a possible compensatory response to decreased mitochondrial metabolic function and a greater potential for reactive oxygen species (ROS) generation. Our findings highlight that the response of aging-impaired mitochondria to inflammation may underlie the worsened cardiac functional depression in the aged group during sepsis. Full article

Herein, α-MnO₂-supported Pt-Pd bimetal (xPd-yPt/α-MnO₂; x and y are the weight loadings (wt%) of Pd and Pt, respectively; x = 0, 0.23, 0.47, 0.93, and 0.92 wt%; and y = 0.91, 0.21, 0.46, 0.89, and 0 wt%) catalysts were prepared using the polyvinyl alcohol-protected NaBH₄ reduction method. The physicochemical properties of the catalysts were determined by means of various techniques and their catalytic activities for toluene oxidation were evaluated. It was found that among the xPd-yPt/α-MnO₂ samples, 0.93Pd-0.89Pt/α-MnO₂ showed the best catalytic performance, with the toluene oxidation rate at 156 °C (r_cat) and space velocity = 60,000 mL/(g h) being 6.34 × 10⁻⁴ mol/(g s), much higher than that of 0.91Pt/α-MnO₂ (1.31 × 10⁻⁴ mol/(g s)) and that of 0.92Pd/α-MnO₂ (6.13 × 10⁻⁵ mol/(g s)) at the same temperature. The supported Pd-Pt bimetallic catalysts possessed higher Mn³⁺/Mn⁴⁺ and O_ads/O_latt molar ratios, which favored the enhancement in catalytic activity of the supported Pd-Pt bimetallic catalysts. Furthermore, the 0.47Pd-0.46Pt/α-MnO₂ sample showed better resistance to sulfur dioxide poisoning. The partial deactivation of 0.47Pd-0.46Pt/α-MnO₂ was attributed to the formation of sulfate species on the sample surface, which covered the active site of the sample, thus decreasing its toluene oxidation activity. In addition, the in situ DRIFTS results demonstrated that benzaldehyde and benzoate were the intermediate products of toluene oxidation. Full article

The rhizosphere microbiome plays an important role in carbon- and nitrogen-cycling in soil and in the stress response of plants. It also affects the function of the ammonium transporter (AmtB) that senses nitrogen levels inside and outside the cells of the associative nitrogen-fixing bacterium GXGL-4A. However, the potential mechanism of the interaction between the AmtB deletion mutant of GXGL-4A (∆amtB) and microorganisms in the rhizosphere of plants under low-nitrogen stress is still unclear. As revealed by transcriptome analyses, mutation of the amtB gene in GXGL-4A resulted in a significant up-regulation of many functional genes associated with nitrogen fixation and transportation at transcription level. The application of ∆amtB changed the nitrogen level in the rhizosphere of cucumber seedlings and reshaped the microbial community structure in the rhizosphere, enriching the relative abundance of Actinobacteriota and Gemmatimonadota. Based on bacterial functional prediction analyses, the metabolic capacities of rhizobacteria were improved after inoculation of cucumber seedlings with the original strain GXGL-4A or the ∆amtB mutant, resulting in the enhancement of amino acids, lipids, and carbohydrates in the cucumber rhizosphere, which promoted the growth of cucumber plants under a low-nitrogen stress condition. The results contribute to understanding the biological function of gene amtB, revealing the regulatory role of the strain GXGL-4A on cucumber rhizosphere nitrogen metabolism and laying a theoretical foundation for the development of efficient nitrogen-fixing bacterial agents for sustainable agricultural production. Full article

Drought stress severely limits the productivity of sweet potato (Ipomoea batatas L.), yet the stage-specific molecular mechanisms of its adaptation remain poorly understood. Therefore, we integrated transcriptomics and extensive targeted metabolomics analysis to investigate the drought responses of the sweet potato cultivar ‘Luoyu 11’ during the branching and tuber formation stage (DS1) and the storage root expansion stage (DS2) under controlled drought conditions (45 ± 5% field capacity). Transcriptome analysis identified 8292 and 13,509 differentially expressed genes in DS1 and DS2, respectively, compared with the well-watered control (75 ± 5% field capacity). KEGG enrichment analysis revealed the activation of plant hormone signaling, carbon metabolism, and flavonoid biosynthesis pathways, and more pronounced transcriptional changes were observed during the DS2 stage. Metabolomic analysis identified 415 differentially accumulated metabolites across the two growth periods, with flavonoids being the most abundant (accounting for 30.3% in DS1 and 23.7% in DS2), followed by amino acids and organic acids, which highlighted their roles in osmotic regulation and oxidative stress alleviation. Integrated omics analysis revealed stage-specific regulation of flavonoid biosynthesis under drought stress. Genes such as CYP75B1 and IF7MAT were consistently downregulated, whereas flavonol synthase and glycosyltransferases exhibited differential expression patterns, which correlated with the selective accumulation of trifolin and luteoloside. Our findings provide novel insights into the molecular basis of drought tolerance in sweet potato and offer actionable targets for breeding and precision water management in drought-prone regions. Full article

Accurate cloud segmentation is critical for astronomical observations and solar forecasting. However, traditional threshold- and texture-based methods suffer from limited accuracy (65–80%) under complex conditions such as thin cirrus or twilight transitions. Although the deep-learning segmentation method based on U-Net effectively captures low-level and high-level features and achieves significant progress in accuracy, current methods still lack interpretability and multi-scale feature integration and usually produce fuzzy boundaries or fragmented predictions. In this paper, we propose multi-scale CAM, an explainable AI (XAI) framework that integrates class activation mapping (CAM) with hierarchical feature fusion to quantify pixel-level attention across hierarchical features, thereby enhancing the model’s discriminative capability. To achieve precise segmentation, we integrate CAM into an improved U-Net architecture, incorporating multi-scale CAM attention for adaptive feature fusion and dilated residual modules for large-scale context extraction. Experimental results on the SWINSEG dataset demonstrate that our method outperforms existing state-of-the-art methods, improving recall by 3.06%, F1 score by 1.49%, and MIoU by 2.21% over the best baseline. The proposed framework balances accuracy, interpretability, and computational efficiency, offering a trustworthy solution for cloud detection systems in operational settings. Full article

Increased antimicrobial resistance requires effective ways to overcome the global challenge of bacterial infections, including methicillin-resistant Staphylococcus aureus (MRSA). From the emergence of MRSA to its continued evolution, it is important to explore this pathogen from fresh perspectives and develop corresponding coping strategies to counter its growing threat. New coping strategies are continuously emerging, including but not limited to enhancing penetration capabilities or targeting their virulence. This review summarizes the epidemiological characteristics, drug resistance mechanisms, and therapeutic strategies of MRSA that have emerged over the past fifteen years. The focus of this paper is to explore the promising applications and current limitations of novel MRSA control strategies. This review serves as a key resource for treating MRSA infections and discussing novel strategies to overcome bacterial drug resistance. Full article

Photovoltaic (PV) systems are the core technology for implementing net-zero carbon emissions by 2050. The performance of PV systems is strongly influenced by environmental factors, including irradiance, temperature, and shading, which makes it difficult to characterize the nonlinear and multi-coupling behavior of the systems. Accurate modeling is essential for reliable performance prediction and lifespan estimation. To address this challenge, a novel metaheuristic algorithm called shuffled puma optimizer (SPO) is deployed to perform parameter extraction and optimal configuration identification across four PV models. The robustness and stability of SPO are comprehensively evaluated through comparisons with advanced algorithms based on best fitness, mean fitness, and standard deviation. The root mean square error (RMSE) obtained by SPO for parameter extraction are 8.8180 × 10⁻⁴, 8.5513 × 10⁻⁴, 8.4900 × 10⁻⁴, and 2.3941 × 10⁻³ for the single diode model (SDM), double diode model (DDM), triple diode model (TDM), and photovoltaic module model (PMM), respectively. A one-factor-at-a-time (OFAT) sensitivity analysis is employed to assess the relative importance of undetermined parameters within each PV model. The SPO-based modeling framework enables high-accuracy PV performance prediction, and its application to sensitivity analysis can accurately identify key factors that lead to reduced computational cost and improved adaptability for integration with energy management systems and intelligent electric grids. Full article

A cable-driven hybrid mobile robot is a kind of robot consisting of two modules connected in series, which uses multiple parallel cables to drive the moving platforms. Cable-driven robots benefit from a large workspace, low inertia, excellent dynamic performance due to the lightweight and high extensibility of cables, making them ideal for a wide range of applications, such as sports cameras, large radio telescopes, and planetary exploration. Considering the fundamental dynamic constraint imposed by the unilateral constraint of cables, the workspace and dynamic modeling for cable-driven robots require specialized study. In this paper, a novel cable-driven hybrid robot, which has two motion patterns, is designed, and an arc intersection method for analyzing workspace is applied to solve the robot workspace of two motion patterns. Based on the workspace analysis, a dynamic model for the cable-driven hybrid robot is established, laying the foundation for subsequent trajectory planning. Simulation results in MATLAB R2021a demonstrate that the cable-driven hybrid robot has a large workspace in both motion patterns and is capable of meeting various motion requirements, indicating promising application potential. Full article

Laizhou Bay, a semi-enclosed bay, is prone to storm surges from cold waves due to its geographic and environmental characteristics. This study uses satellite data, in situ measurements, and the MIKE numerical model to analyze storm surges along Laizhou Bay’s coast under no-dike conditions. It examines the surges caused by cold waves with different intensities and directions. This study provides the storm surge disaster risk levels along Laizhou Bay’s coast. The results show that the maximum sustained wind speed during cold waves is distributed between the NW and NE. The NE wind direction causes the most severe storm surge along Laizhou Bay. Under NE-directed cold waves with level 12 wind, the maximum risk areas for Level III and IV are approximately 1341 km² and 1294 km², respectively. Dongying, Shouguang, and Hanting exhibit large Level I and II risk zones. The maximum seawater intrusion distance along the Kenli coast is about 41 km. The coastal segment from Kenli to Changyi is most severely affected by storm surges. It is recommended to effectively maintain and heighten seawalls along this segment to mitigate storm surge disasters caused by strong NE winds. Full article

Ultra-high-temperature and pressure downhole environments pose challenges for conventional electronic instruments to adapt to high-temperature formations, thereby restricting the application of downhole electronic tool technology in deep and ultra-deep wells. Given the aforementioned limitation of electronic inclination measurement systems, specifically their poor temperature resistance, this study proposes a novel shunt flow control method. This method employs a mechanical structure to overcome temperature constraints: gravitational torque generated by the mechanical structure is utilized to control valve opening and regulate flow rate. By converting sensed well inclination information into changes in flow rate, this approach enables the transformation of well inclination sensing and its associated signals. In this study, a kinetic analysis model of the shunt-regulating valve spool was established. Using computational fluid dynamics (CFD) simulations, the flow characteristics of the regulating spool were analyzed under varying valve openings. The structure of the flow control valve was optimized with the goal of maximizing internal flow. Finally, the reliability of the designed structure for well deviation sensing and flow control was verified using simulation experimental studies and theoretical analyses. Full article

Background: Parkinson’s disease (PD) involves progressive dopaminergic neuron degeneration and motor deficits. Oligodendrocyte dysfunction contributes to PD pathogenesis through impaired myelination. Methods: Single-nucleus RNA sequencing (snRNA-seq) of PD mice revealed compromised oligodendrocyte differentiation and STAT5B downregulation. Pseudotemporal trajectory analysis via Monocle2 demonstrated impaired oligodendrocyte maturation in PD oligodendrocytes, correlating with reduced myelin-related gene expression (Sox10, Plp1, Mbp, Mog, Mag, Mobp). DoRothEA-predicted regulon activity identified STAT5B as a key transcriptional regulator. Results: Oligodendrocyte-specific STAT5B activation improved myelin integrity, as validated by Luxol Fast Blue staining and transmission electron microscopy; attenuated dopaminergic neuron loss; and improved motor function. Mechanistically, STAT5B binds the MBP promoter to drive transcription, a finding confirmed by the luciferase assay, while the DNMT3A-mediated hypermethylation of the STAT5B promoter epigenetically silences its expression, as verified by MethylTarget sequencing and methylation-specific PCR. Conclusions: DNMT3A inhibited the expression of STAT5B by affecting its methylation, which reduced the transcription of MBP, caused oligodendrocyte myelin damage, and eventually led to dopamine neuron damage and motor dysfunction in an MPTP-induced mouse model. This DNMT3A-STAT5B-MBP axis underlies PD-associated myelin damage, connecting epigenetic dysregulation with oligodendrocyte dysfunction and subsequent PD pathogenesis. Full article

UDP-glycosyltransferases (UGTs) play essential roles in various biological processes, such as phytohormone homeostasis, abiotic stress adaptation, and secondary metabolite biosynthesis. Populus euphratica is a model species for investigating stress adaptation; however, the PeUGT gene family has yet to be systematically characterized. Here, we identified 134 UGT genes in P. euphratica. Phylogenetic analysis classified these genes into 16 major groups (A–P), and UGT genes within the same groups showed similar structural characteristics. Tandem duplication events were identified as the predominant mechanism driving the expansion of the PeUGT family. Cis-acting element analysis revealed an enrichment of motifs associated with developmental regulation, light response, phytohormone signaling, and abiotic stress in the promoters of PeUGT genes. Expression profiling demonstrated spatiotemporal regulation of the PeUGT genes under drought stress. Among them, PeUGT110 was significantly induced by PEG treatment in the leaf, root, and stem tissues of P. euphratica. Overexpression of PeUGT110 enhanced drought tolerance in transgenic Arabidopsis. Furthermore, the PeUGT110-OE lines exhibited reduced malonaldehyde accumulation, elevated proline content, higher superoxide dismutase activity, and upregulated expression of stress-related genes under drought stress. The results demonstrated that PeUGT110 plays a critical role in plant drought resistance. These findings establish a foundation for elucidating the function of PeUGT genes. Full article