Search Results (50)

High-resolution numerical weather prediction requires accurate cloud microphysical initial conditions to enhance forecasting capabilities for high-impact severe weather events such as convective storms. This study integrated Fengyun-2 (FY-2) geostationary satellite data (equivalent blackbody temperature and total cloud cover) and next-generation 3D weather radar reflectivity from the China Meteorological Administration (CMA) to construct cloud microphysical initial fields and evaluate their impact on the CMA-MESO 3 km regional model. An analysis of the catastrophic rainfall event in Henan on 20 July 2021, and a 92-day continuous experiment (May–July 2024) revealed that assimilating cloud microphysical variables significantly improved precipitation forecasting: the equitable threat scores (ETSs) for 1 h forecasts of light, moderate, and heavy rain increased from 0.083, 0.043, and 0.007 to 0.41, 0.36, and 0.217, respectively, with average hourly ETS improvements of 21–71% for 2–6 h forecasts and increases in ETSs for light, moderate, and heavy rain of 7.5%, 9.8%, and 24.9% at 7–12 h, with limited improvement beyond 12 h. Furthermore, the root mean square error (RMSE) of the 2 m temperature forecasts decreased across all 1–72 h lead times, with a 4.2% reduction during the 1–9 h period, while the geopotential height RMSE reductions reached 5.8%, 3.3%, and 2.0% at 24, 48, and 72 h, respectively. Additionally, synchronized enhancements were observed in 10 m wind prediction accuracy. These findings underscore the critical role of cloud microphysical initialization in advancing mesoscale numerical weather prediction systems. Full article

The influenza A virus (IAV) is a major cause of recurrent seasonal epidemics and global pandemics, posing a significant threat to public health. Although lycorine has demonstrated broad-spectrum antiviral activity, its specific mechanisms of action against IAV remain incompletely understood. In this study, we characterized the potent inhibitory effects of lycorine on seasonal and drug-resistant IAV subtypes (H1N1/H3N2) as well as the influenza B virus, showing its ability to suppress viral mRNA, viral titers, and M2 protein expression across multiple cell lines. Time-of-addition and time-course assays revealed that lycorine exerts multiphasic interference, and the critical late stage of the IAV life cycle aroused our interest to study this further. Mechanistically, we discovered that lycorine specifically interferes with the de novo synthesis of nucleoporin Nup93, thereby disrupting the nuclear export of viral nucleoprotein (NP). These findings not only establish lycorine as a promising broad-spectrum anti-influenza candidate but also provide new insights for developing host-targeted antiviral strategies. Full article

Heart failure with preserved ejection fraction (HFpEF), marked by cardiac diastolic dysfunction, contributes to half of all heart failure cases globally and poses a significant public health challenge. Effective therapies for HFpEF are rare, largely due to its complex and heterogeneous pathophysiology, which often involves multiple comorbidities. Berberine (BBR), an isoquinoline alkaloid, has demonstrated beneficial effects on multiple metabolic and cardiovascular disorders; however, its impact on cardiac diastolic dysfunction in HFpEF remains poorly understood. In this study, we utilized a rat model of HFpEF induced by a sustained high-fat/high-sucrose (HFHS) diet to explore the impact and mechanisms of BBR on diastolic dysfunction. The results revealed that BBR administration effectively alleviated cardiac diastolic dysfunction and alleviated extracardiac comorbidities, including increased weight, impaired glucose tolerance, hypercholesterolemia and hypertension, in rats fed an HFHS diet. Furthermore, BBR mitigated myocardial inflammation, oxidative stress, microvascular endothelial dysfunction, and notably restored the disturbed NO-cGMP-PKG pathway. Additionally, BBR reduced myocardial fibrosis and inhibited the abnormally activated TGF-β/Smads signaling. Moreover, BBR attenuated the systemic inflammation and corrected immune dysregulation in an HFHS diet-fed rats. Our study suggests that BBR exhibits multi-beneficial effects in the prevention and management of HFpEF, demonstrating its potential as a holistic therapeutic candidate for HFpEF. Full article

Superovulation and embryo transfer are key technologies to improve the reproductive ability of female animals and enhance the efficiency of livestock production. However, poor-quality oocytes or abnormal fluctuations of hormone levels caused by superovulation affect the embryonic development environment, which may lead to a significant decline in the number and quality of transferable embryos, thus reducing the efficiency of superovulation. In this study, nicotinamide adenine dinucleotide (NAD⁺) was injected into Huaxi cows during the superovulation period to observe the proliferation and apoptosis of transplanted embryos. We examined the proliferation, apoptosis, reactive oxygen species (ROS) and mitochondrial membrane potential of cumulus cells and oocytes directly treated with NAD⁺ and investigated the potential mechanism of NAD⁺ to improve the superovulation efficiency by serum metabolomics and single-cell RNA sequencing. The results show that the addition of NAD⁺ significantly increased the quantity and quality of transferable embryos after superovulation. Differential metabolites during estrus synchronization and embryo flushing are enriched in glycerophospholipid metabolic pathways, suggesting that NAD⁺ can regulate lipid metabolic pathways. We found that NAD⁺ optimized the secretion levels of the steroid hormone estradiol (E2) and progesterone (P4) during superovulation by regulating the activity of cumulus cells. In oocytes, we found that NAD⁺ can inhibit apoptosis, scavenge ROS, and enhance mitochondrial function, thereby promoting oocyte maturation and enhancing embryo developmental potential. In conclusion, NAD⁺ significantly improved the superovulation ability of Huaxi cattle and provides an effective way for animal husbandry to improve the yield of high-quality embryos. Full article

Liver fibrosis, caused by chronic hepatic injury, is a major threat to human health worldwide, as there are no specific drugs available for its treatment. Natural compounds, such as berberine (BBR) and quercetin (QR), have shown the ability to regulate energy metabolism and protect the liver without significant adverse effects. Additionally, combination therapy (the cocktail therapy approach), using multiple drugs, has shown promise in treating complicated conditions, including liver injury. In this study, we prepared a salt formulation of BBR and QR (BQS) to enhance their combined effect on liver fibrosis. The formation of BQS was confirmed using various analytical techniques, including nuclear magnetic resonance spectroscopy (NMR), differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR), powder X-ray diffractometry (PXRD), and scanning electron microscopy (SEM). The results demonstrated that the dissolution efficiency and bioavailability of QR significantly increased in the BQS form, aligning with that of BBR, compared to the physically mixed (BQP) form. Moreover, BQS exhibited a superior inhibitory effect on fibrosis compared to BQP in the human hepatic stellate cell line LX-2 by modulating lipid accumulation, inflammation, apoptosis, and the cell cycle. Furthermore, in a mouse model of hepatic fibrosis induced by methionine and choline-deficient (MCD) diets, BQS demonstrated enhanced anti-fibrotic activities compared to BQP. These findings suggest that BQS holds promise as a potential alternative treatment for liver fibrosis. Importantly, this study provides novel insights into achieving a cocktail effect through the salt formation of two or more drugs. The results highlight the potential of salt formulations in enhancing the therapeutic efficacy and consistent biological processes of drug combinations. Full article

The phyllosphere represents the largest biological surface on Earth and serves as an untapped reservoir of functional microbiota. The phyllosphere microbiome has the potential to mitigate plant diseases; however, limited information exists regarding its role in maintaining plant health. In this study, metagenomic sequencing was employed to analyze the microbiomes of the adaxial and abaxial leaf surfaces of healthy (CKWT) and diseased (EWT) maize, with the aim of dissecting the influence of Exserohilum turcicum on phyllosphere microbiome function. E. turcicum altered the alpha and beta diversity of the phyllosphere microbiome, with the Shannon diversity and Chao1 index values significantly reduced in EWT. More beneficial microbes accumulated in the CKWT phyllosphere, whereas pathogenic microbes decreased. E. turcicum may have altered the balance between commensal and pathogenic microorganisms. The species and abundances of microorganisms on the two sets of leaf surfaces were also altered after inoculation with E. turcicum. Further analysis of disease-resistance-related metabolic pathways and abundances of antibiotic-resistance genes revealed that E. turcicum altered the abundance of the functional microbiome and modified the microbiome differences between adaxial and abaxial leaf surfaces. In conclusion, the results reveal that microbial diversity in the maize phyllosphere can influence the microbiome and regulate microbial functions to support plant health. These findings enhance our understanding of how E. turcicum affects the phyllosphere microbiome and provide a theoretical basis for biological control of E. turcicum. Full article

Soil salinization is one of the primary factors contributing to land degradation in arid areas, severely restricting the sustainable development of agriculture and the economy. Satellite remote sensing is essential for real-time, large-scale soil salinity content (SSC) evaluation. However, some satellite images have low temporal resolution and are affected by weather conditions, leading to the absence of satellite images synchronized with ground observations. Additionally, some high-temporal-resolution satellite images have overly coarse spatial resolution compared to ground features. Therefore, the limitations of these spatiotemporal features may affect the accuracy of SSC evaluation. This study focuses on the arable land in the Manas River Basin, located in the arid areas of northwest China, to explore the potential of integrated spatiotemporal data fusion and deep learning algorithms for evaluating SSC. We used the flexible spatiotemporal data fusion (FSDAF) model to merge Landsat and MODIS images, obtaining satellite fused images synchronized with ground sampling times. Using support vector regression (SVR), random forest (RF), and convolutional neural network (CNN) models, we evaluated the differences in SSC evaluation results between synchronized and unsynchronized satellite images with ground sampling times. The results showed that the FSDAF model’s fused image was highly similar to the original image in spectral reflectance, with a coefficient of determination (R²) exceeding 0.8 and a root mean square error (RMSE) below 0.029. This model effectively compensates for the missing fine-resolution satellite images synchronized with ground sampling times. The optimal salinity indices for evaluating the SSC of arable land in arid areas are S3, S5, SI, SI1, SI3, SI4, and Int1. These indices show a high correlation with SSC based on both synchronized and unsynchronized satellite images with ground sampling times. SSC evaluation models based on synchronized satellite images with ground sampling times were more accurate than those based on unsynchronized images. This indicates that synchronizing satellite images with ground sampling times significantly impacts SSC evaluation accuracy. Among the three models, the CNN model demonstrates the highest predictive accuracy in SSC evaluation based on synchronized and unsynchronized satellite images with ground sampling times, indicating its significant potential in image prediction. The optimal evaluation scheme is the CNN model based on satellite image synchronized with ground sampling times, with an R² of 0.767 and an RMSE of 1.677 g·kg⁻¹. Therefore, we proposed a framework for integrated spatiotemporal data fusion and CNN algorithms for evaluating soil salinity, which improves the accuracy of soil salinity evaluation. The results provide a valuable reference for the real-time, rapid, and accurate evaluation of soil salinity of arable land in arid areas. Full article

Enhancing global agricultural sustainability critically requires improving the physicochemical properties of saline–alkali soil. Biochar has gained increasing attention as a strategy due to its unique properties. However, its effect on the physicochemical properties of saline–alkali soil varies significantly. This study uses psychometric meta-analysis across 137 studies to synthesize the findings from 1447 relatively independent data sets. This study investigates the effects of biochar with different characteristics on the top 20 cm of various saline–alkali soils. In addition, aggregated boosted tree (ABT) analysis was used to identify the key factors of biochar influencing the physicochemical properties of saline soils. The results showed that biochar application has a positive effect on improving soil properties by reducing the sodium adsorption ratio (SAR) and the exchangeable sodium percentage (ESP) by 30.31% and 28.88%, respectively, with a notable 48.97% enhancement in cation exchange capacity (CEC). A significant inverse relationship was found between soil salinity (SC) and ESP, while other factors were synergistic. Biochar application to mildly saline soil (<0.2%) and moderately saline soil (0.2–0.4%) demonstrated greater improvement in soil bulk density (SBD), total porosity (TP), and soil moisture content (SMC) compared to highly saline soil (>0.4%). However, the reduction in SC in highly saline soil was 4.9 times greater than in moderately saline soils. The enhancement of soil physical properties positively correlated with higher biochar application rates, largely driven by soil movements associated with the migration of soil moisture. Biochar produced at 401–500 °C was generally the most effective in improving the physicochemical properties of various saline–alkali soils. In water surplus regions, for mildly saline soil with pH < 8.5, mixed biochar (pH 6–8) at 41–80 t ha⁻¹ was the most effective in soil improvement. Moreover, in water deficit areas with soil at pH ≥ 8.5, biochar with pH ≤ 6 applied at rates of >80 t ha⁻¹ showed the greatest benefits. Agricultural residue biochar showed superior efficiency in ameliorating highly alkaline (pH ≥ 8.5) soil. In contrast, the use of mixed types of biochar was the most effective in the amelioration of other soil types. Full article

Recently, developing multi-UAVs to cooperatively pursue a fast-moving target has become a research hotspot in the current world. Although deep reinforcement learning (DRL) has made a lot of achievements in the UAV pursuit game, there are still some problems such as high-dimensional parameter space, the ease of falling into local optimization, the long training time, and the low task success rate. To solve the above-mentioned issues, we propose an improved twin delayed deep deterministic policy gradient algorithm combining the genetic algorithm and maximum mean discrepancy method (GM-TD3) for multi-UAV cooperative pursuit of high-speed targets. Firstly, this paper combines GA-based evolutionary strategies with TD3 to generate action networks. Then, in order to avoid local optimization in the algorithm training process, the maximum mean difference (MMD) method is used to increase the diversity of the policy population in the updating process of the population parameters. Finally, by setting the sensitivity weights of the genetic memory buffer of UAV individuals, the mutation operator is improved to enhance the stability of the algorithm. In addition, this paper designs a hybrid reward function to accelerate the convergence speed of training. Through simulation experiments, we have verified that the training efficiency of the improved algorithm has been greatly improved, which can achieve faster convergence; the successful rate of the task has reached 95%, and further validated UAVs can better cooperate to complete the pursuit game task. Full article

Potential transformers are vital for measuring and protecting the power grid. Their accuracy and reliability directly impact the stability and security of the power system. To address the issues with traditional high-precision potential transformer calibrators, such as cumbersome operation and low efficiency, a high-precision potential transformer calibrator has been developed. The calibrator is based on an embedded system architecture of FPGA and ARM. It uses a high-precision current comparator along with feedback control technology. By monitoring and adjusting the error feedback voltage, it can perform the automated calibration of potential transformers with an accuracy class of 0.0001. The measurement ranges from 0.00001% to 200.0%. This study can be adapted to meet the development needs of modern digital measurement systems. Full article

Metabolic syndrome (MetS) is a cluster of risk factors for cardiovascular diseases (CVDs) that has become a global public health problem. Puerarin (PUE), the principal active compound of Pueraria lobata, has the effects of regulating glucose and lipid metabolism and protecting against cardiovascular damage. This study aimed to investigate whether dietary supplementation with PUE could ameliorate MetS and its associated cardiovascular damage. Rats were randomly divided into three groups: the normal diet group (NC), the high-fat/high-sucrose diet group (HFHS), and the HFHS plus PUE diet group (HFHS-PUE). The results showed that PUE-supplemented rats exhibited enhanced glucose tolerance, improved lipid parameters, and reduced blood pressure compared to those on the HFHS diet alone. Additionally, PUE reversed the HFHS-induced elevations in the atherogenic index (AI) and the activities of serum lactate dehydrogenase (LDH) and creatine kinase (CK). Ultrasonic evaluations indicated that PUE significantly ameliorated cardiac dysfunction and arterial stiffness. Histopathological assessments further confirmed that PUE significantly mitigated cardiac remodeling, arterial remodeling, and neuronal damage in the brain. Moreover, PUE lowered systemic inflammatory indices including C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune-inflammation index (SII). In conclusion, dietary supplementation with PUE effectively moderated metabolic disorders, attenuated systemic inflammation, and minimized cardiovascular damage in rats with MetS induced by an HFHS diet. These results provide novel insights into the potential benefits of dietary PUE supplementation for the prevention and management of MetS and its related CVDs. Full article

Compounds that potentiate the activity of clinically available antibiotics provide a complementary solution, except for developing novel antibiotics for the rapid emergence of multidrug-resistant Gram-negative bacteria (GNB). We sought to identify compounds potentiating polymyxin B (PMB), a traditional drug that has been revived as the last line for treating life-threatening GNB infections, thus reducing its nephrotoxicity and heterogeneous resistance in clinical use. In this study, we found a natural product, sanguinarine (SA), which potentiated the efficacy of PMB against GNB infections. The synergistic effect of SA with PMB was evaluated using a checkerboard assay and time–kill curves in vivo and the murine peritonitis model induced by Escherichia coli in female CD-1 mice in vivo. SA assisted PMB in accelerating the reduction in bacterial loads both in vitro and in vivo, improving the inflammatory responses and survival rate of infected animals. The subsequent detection of the intracellular ATP levels, membrane potential, and membrane integrity indicated that SA enhanced the bacterial-membrane-breaking capacity of PMB. A metabolomic analysis showed that the inhibition of energy metabolism, interference with nucleic acid biosynthesis, and the blocking of L-Ara4N-related PMB resistance may also contribute to the synergistic effect. This study is the first to reveal the synergistic activity and mechanism of SA with PMB, which highlights further insights into anti-GNB drug development. Full article

The temperature stress caused by the large temperature difference is the main factor causing harmful cracks in large-volume concrete. The introduction of admixtures is beneficial to reduce the temperature difference inside and outside the large-volume concrete. This study investigated the mechanism of how citric acid-modified chitosan (CAMC) affects the hydration heat release process and hydration products of composite cementitious materials. Through methods such as hydration heat, X-ray diffraction (XRD), mercury intrusion porosimetry (MIP), scanning electron microscopy (SEM), and nuclear magnetic resonance (NMR), the mechanism of how CAMC controls the hydration heat release process and hydration products of composite cementitious materials was revealed. The results show that the addition of CAMC delayed the hydration process of cementitious materials without affecting the type of hydration products but affected the content of each phase of hydration products. As the hydration process proceeded, the total porosity of all samples decreased, the volume of large pores decreased, and the volume of small pores increased. As the content of CAMC increased, the pore diameter of the hardened paste gradually became smaller, the proportion of large pores decreased, and the later hydration microstructure became more dense. The increase in CAMC dosage resulted in a decrease in the peak intensity of Q² in the paste, indicating that Al atoms in Q² (¹Al) existed in the form of Alcoordination, which proves that CAMC reduced its hydration degree and delayed cement hydration. Full article

Bored piles comprise an advanced pile foundation technology that has the advantages of high bearing capacity, fast construction speed, stable construction technology, and no noise or mud pollution. To study the applicability of bored piles to collapsible loess sites, the compaction effect and load-bearing characteristics of bored piles before and after immersion were studied via a full-scale field test combined with the theory of hole expansion. The results indicate that when the pile spacing is 1.0, 1.25, and 1.5 m, the average dry density of the soil between piles increases by 23.8%, 18.5%, and 3.1%, respectively, compared with that of untreated foundation soil. When bored piles are used to treat deep collapsible loess foundations, the reasonable pile spacing to eliminate the collapsibility of the loess foundation is 2.5 times the pile diameter. It is feasible to estimate the effective compaction range using the pore expansion theory, and the effective compaction coefficients of similar sites are given. The positive friction of bored piles in the collapsible loess area is more than 95.5 kPa, which increases by more than 48.5% compared with that of non-extruded piles. Therefore, the bearing capacity of a single pile is significantly improved, and it is an effective treatment method for collapsible loess areas. Under immersion, the pile side negative friction did not change significantly with a pile diameter of approximately 27 kPa, and the increase was approximately 14% compared with that of non-extruded piles. Consequently, to avoid the adverse effects of negative friction resistance on the bearing capacity of pile foundations and to fully utilize the technical advantages of bored piles, it is necessary to eliminate or partially eliminate site collapsibility before applying bored piles. The results can provide experimental support and theoretical guidance for the popularization and application of screw–squeeze piles in deep, collapsible loess areas. Full article

Background: Glioblastoma multiforme is the most common primary intracranial tumor, with a high degree of malignancy, poor therapeutic effect, and poor prognosis. According to previous studies, CHI3L1 and EMP3 are two independent tumor predictors that are of great significance for the prognostic prediction of other tumors, and their expression levels may be related to the prognosis of glioma patients. Methods: using Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), the Chinese Glioma Genome Atlas (CGGA), cBioPortal, LinkedOmics, and other databases, 693 glioma patients were screened to analyze the relationship between EMP3 and CHI3L1 expression and prognosis in glioma patients. Results: low-grade glioma patients with a low expression of EMP3/CHI3L1 had a better prognosis, and the combination of EMP3/CHI3L1 is a new predictor for glioma patients. Conclusion: We used the TCGA and CGGA databases to analyze the effect of EMP3 and CHI3L1 expression on the prognosis of glioma patients and their correlation with gene expression using bioinformation analysis. The results showed that low-grade glioma patients with a low expression of EMP3 and CHI3L1 had a better prognosis, and EMP3 and CHI3L1 co-expression genes were correlated. The combination of these two factors could be a new prognostic index for glioma patients. Full article