Search Results (105)

Alzheimer’s disease (AD) is a neurodegenerative disease with a multifaceted pathogenesis, which remains elusive, seriously affecting the quality of life of elderly patients and placing a heavy burden on affected individuals, their families, and society. As third-party synapses in brain networks, astrocytes play an important role in maintaining the normal function of neural networks, which contribute to the abnormal function of networks in AD. In recent years, numerous studies have shown that clusterin, a protein expressed by astrocytes, can participate in the progression of AD. Clusterin plays a significant role in many pathological processes of AD, such as lipid metabolism, AD pathological features, the imbalance in neural circuit excitatory inhibition, and neuroinflammation. Therefore, delving deeper into the association between clusterin and AD will help us to understand the mechanisms of disease better and provide a theoretical basis for early diagnosis and the development of treatment strategies for AD. Full article

Phase-sensitive surface plasmon resonance (SPR) detection is widely employed in molecular dynamics studies and SPR imaging owing to its real-time capability, high sensitivity, and compatibility with imaging systems. A key research objective is to achieve higher measurement resolution of refractive index under optimal dynamic range conditions. We present an enhanced SPR phase imaging system combining a quad-polarization filter array for phase differential detection with a novel polarization pair, block matching, and 4D filtering (PPBM4D) algorithm to extend the dynamic range and enhance resolution. By extending the BM3D framework, PPBM4D leverages inter-polarization correlations to generate virtual measurements for each channel in the quad-polarization filter, enabling more effective noise suppression through collaborative filtering. The algorithm demonstrates 57% instrumental noise reduction and achieves 1.51 × 10⁻⁶ RIU resolution (1.333–1.393 RIU range). The system’s algorithm performance is validated through stepwise NaCl solution switching experiments (0.0025–0.08%) and protein interaction assays (0.15625–20 μg/mL). This advancement establishes a robust framework for high-resolution SPR applications across a broad dynamic range, particularly benefiting live-cell imaging and high-throughput screening. Full article

Objective: Our objective was to explore the regulatory mechanism of salt processing on the metabolome of the raspberry and its potential efficacy against diabetic nephropathy (DN), providing metabolomic and network pharmacological evidence for the scientific connotation of traditional Chinese medicine processing. Methods: Ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS)-based metabolomics was used to compare the metabolic profiles between raw and salt-processed raspberries. Network pharmacology was applied to screen the common targets of the active components in the salt-processed raspberry and DN-related pathways, followed by in vitro cell experiments to validate the regulation of the MAPK signaling pathway. Results: The metabolomic analysis identified 80 differentially expressed metabolites, among which 13 key components (VIP ≥ 1, FC ≥ 2) were significantly altered, including enriched flavonoids (e.g., luteolin-7-O-glucoside), triterpenoid saponins (Raspberryides H/F), and phenolic acids (ellagic acid). The network pharmacology revealed that the salt-processed raspberries regulated the DN-related pathways through 122 common targets, with the core nodes focusing on the signaling molecules (e.g., AKT1, EGFR) involved in the MAPK signaling pathway and apoptosis regulation. The in vitro experiments confirmed that the salt-processed raspberry extract (160–640 μg/mL) significantly inhibited the phosphorylation levels of p38/ERK/JNK in high-glucose-induced renal cells. Conclusions: This study firstly combines metabolomics and network pharmacology to reveal the regulatory mechanism of salt processing on the active components of raspberries. The salt-processing technology enhanced the inhibitory effect of raspberries on the MAPK signaling pathway, thereby ameliorating the progression of DN. These findings provide scientific support for establishing a metabolomics-based quality control system for traditional Chinese medicine processing. The current findings are primarily based on in vitro models, and in vivo validation using DN animal models is essential to confirm the therapeutic efficacy and safety of salt-processed raspberries. Full article

Background/Objectives: The role of glycogen metabolism in diabetic kidney disease (DKD) remains unclear. This study investigated the therapeutic potential of asiatic acid (AA) on glycogen metabolism in DKD and its underlying mechanisms. Methods: A DKD mouse model was established using a high-fat diet and streptozotocin, followed by AA treatment for 8 weeks. Network pharmacology and molecular docking identified STBD1 as a potential target of AA, and its overexpression in mice was performed. Results: AA reduced blood glucose levels and the urinary albumin-to-creatinine ratio (UACR) and downregulated TGFβ-1, KIM-1, and PDK4. Additionally, AA treatment reversed abnormal glycogen accumulation and restored STBD1 expression. Network pharmacology and molecular docking identified STBD1 as a potential target of AA, and its overexpression in mice demonstrated similar beneficial effects. Gene enrichment analysis revealed that STBD1 is involved in key metabolic pathways related to DKD. Conclusions: These findings suggest that AA alleviates renal damage in DKD, possibly through modulation of STBD1, highlighting its therapeutic potential and the critical role of STBD1 in renal glycophagy. Full article

Soil salinization hinders plant growth and agricultural production, so breeding salt-tolerant crops is an economical way to exploit saline–alkali soils. However, the specific metabolites and associated pathways involved in salt tolerance of the dandelion have not been clearly elucidated so far. Here, we compared the transcriptome and metabolome responses of 0.7% NaCl-stressed dandelion ‘BINPU2’ (variety A) and ‘TANGHAI’ (variety B). Our results showed that 222 significantly altered metabolites mainly enriched in arginine biosynthesis and pyruvate metabolism according to a KEGG database analysis in variety A, while 147 differential metabolites were predominantly enriched in galactose metabolism and the pentose phosphate pathway in variety B. The transcriptome data indicated that the differentially expressed genes (DEGs) in variety A were linked to secondary metabolite biosynthesis, phenylpropanoid biosynthesis, and photosynthesis–antenna proteins. Additionally, KEGG annotations revealed the DEGs had functions assigned to general function prediction only, post-translation modification, protein turnover, chaperones, and signal transduction mechanisms in variety A. By contrast, the DEGs had functions assigned to variety B as plant–pathogen interactions, phenylpropanoid biosynthesis, and photosynthesis–antenna proteins, including general function prediction, signal transduction mechanisms, and secondary metabolite biosynthesis from the KOG database functional annotation. Furthermore, 181 and 162 transcription factors (TFs) expressed under saline stress conditions specifically were detected between varieties A and B, respectively, representing 36 and 37 TF families. Metabolomics combined with transcriptomics revealed that salt stress induced substantial changes in terpenoid metabolites, ubiquinone biosynthesis metabolites, and pyruvate metabolites, mediated by key enzymes from the glycoside hydrolase family, adenylate esterases family, and P450 cytochrome family at the mRNA and/or metabolite levels. These results may uncover the potential salt-response mechanisms in different dandelion varieties, providing insights for breeding salt-tolerant crop plants suitable for saline–alkali land cultivation. Full article

Owing to the rapid increase in the amount of legal text data and the increasing demand for intelligent processing, multi-label legal text recognition is becoming increasingly important in practical applications such as legal information retrieval and case classification. However, traditional methods have limitations in handling the complex semantics and multi-label characteristics of legal texts, making it difficult to accurately extract feature and effective category information. Therefore, this study proposes a novel multi-head hierarchical attention framework suitable for multi-label legal text recognition tasks. This framework comprises a feature extraction module and a hierarchical module. The former extracts multi-level semantic representations of text, while the latter obtains multi-label category information. In addition, this study proposes a novel hierarchical learning optimization strategy that balances the learning needs of multi-level semantic representation and multi-label category information through data preprocessing, loss calculation, and weight updating, effectively accelerating the convergence speed of framework training. We conducted comparative experiments on the legal domain dataset CAIL2021 and the general multi-label recognition datasets AAPD and Web of Science (WOS). The results indicate that the method proposed in this study is significantly superior to mainstream methods in legal and general scenarios, demonstrating excellent performance. The study findings are expected to be widely applied in the field of intelligent processing of legal information, improving the accuracy of intelligent classification of judicial cases and further promoting the digitalization and intelligence process of the legal industry. Full article

The northwestern slope of the Dongdao Platform in the Xisha Sea exhibits a complex geomorphological structure. Utilizing high-resolution multibeam bathymetric data and 2D seismic profiles, this study systematically reconstructs the slope morphology and its evolutionary processes. The study area displays a distinct threefold zonation: the upper slope (160–700 m water depth) has a steep gradient of 15°–25°, characterized by deeply incised V-shaped channels and slump deposits, primarily shaped by gravity-driven erosion; the middle slope (700–1200 m water depth) features a gentler gradient of 10°–15°, where channels stabilize, adopting U-shaped cross-sections with the development of lateral accretion deposits; the lower slope (1200–1500 m water depth) exhibits a milder gradient of 5°–10°, dominated by a mixture of fine-grained carbonate sediments and hemipelagic mud–marine sediments originating partly from the open ocean and partly from the nearby continental margin. The slope extends from 160 m to 1500 m water depth, hosting the C1–C4 channel system. Seismic facies analysis reveals mass-transport deposits, channel-fill facies, and facies modified by bottom currents—currents near the seafloor that redistribute sediments laterally—highlighting the interplay between fluid activity and gravity-driven processes. The slope evolution follows a four-stage model: (1) the pockmark formation stage, where overpressured gas migrates vertically through chimneys, inducing localized sediment instability and forming discrete pockmarks; (2) the initial channel development stage, during which gravity flows exploit the pockmark chains as preferential erosional pathways, establishing nascent incised channels; (3) the channel expansion and maturation stage, marked by intensified erosion from high-density debris flows, resulting in a stepped longitudinal profile, while bottom-current reworking enhances lateral sediment differentiation; (4) the stable transport stage, wherein the channels fully integrate with the Sansha Canyon, forming a well-connected “platform-to-canyon” sediment transport system. Full article

Swine have emerged as significant reservoirs of antibiotic-resistant strains and genes. To establish a sound rationale for applying quinolone antibiotics in the swine industry, a meta-analysis was performed on the resistance rate of swine-derived Escherichia coli to quinolone antibiotics in China from 2002 to 2022. We systematically searched through three databases, PubMed, Web of Science, and CNKI, and included 53 eligible studies within the specified timeframe. Resistance rates were calculated using a random-effects model and the Freeman–Tukey double-arcsine transformation. The resistance rates observed were as follows: 37% for levofloxacin (95% CI: 27~47%), 43% for ofloxacin (95% CI: 34~51%), 54% for enrofloxacin (95% CI: 46~62%), and 50% for ciprofloxacin (95% CI: 42~58%). Further subgroup analyses illuminated that the resistance rates were higher in mainland China’s eastern regions than in western regions. Additionally, there was no significant decrease in the resistance rate over time in different periods. From 2002 to 2022, Escherichia coli strains from swine in various regions of mainland China exhibited differing degrees of generalized resistance to quinolones. This poses a potential public health risk and underscores the fact that the control of quinolone antibiotics remains a prolonged and ongoing challenge. Full article

Scientific management and environmental regulation of facility strawberries depends on the level of accurate prediction and forecasting of low temperature freezes in plastic greenhouses during winter and spring strawberry cultivation. Accurate identification of potential factors affecting layer-by-layer minimum temperatures in plastic greenhouses and selection of optimal forecasting methods are important for safe strawberry production. However, the identification of important drivers of minimum temperatures in plastic greenhouses and the prediction of potential drivers of use are still unclear. In this study, we used Classification and Regression Tree (CART) to identify the importance of the potential factors affecting the minimum temperatures at different depths and different heights of plastic greenhouses. Random forest (RF), back-propagation (BP), and multiple linear regression (MLR) were used to establish the minimum temperature prediction models for plastic greenhouses at different depths and heights, respectively. The results showed that T_smin10, T_smin25, T_amin150, T_amin320, and T_amin150 were the most important variables explaining the changes in minimum temperatures at heights T_smin25, T_smin10, T_smin2, T_amin150, and T_amin320 respectively. RF, BP performed much better than MLR, as it showed much lower error indices (AE and RMSE) and higher R² than MLR. The superiority of RF and BP in predicting minimum temperatures is related to their ability to deal with non-linear and hierarchical relationships between minimum temperatures and predictors. The low-temperature frost protection and fine management of strawberries in the Changfeng area can be related to the prediction method of minimum temperature in plastic greenhouses constructed in this study. Full article

This study explores the variation in the content of major phenolic acid components in dandelions from different regions, and the potential molecular mechanisms underlying their anti-inflammatory activity. High-performance liquid chromatography (HPLC) was employed to analyze dandelion leaves collected from four different regions in Hebei Province across eight harvest periods. The results indicated that chlorogenic acid had the highest content (0.334–1.963%), suggesting that this could be a key evaluation index for dandelion leaf harvesting. Further molecular docking and molecular dynamics simulations revealed that chlorogenic acid, caffeic acid, and chicoric acid could competitively bind to the key amino acid residues (e.g., PHE-151, ILE-117) of the MD-2 protein, thereby preventing the insertion of lipopolysaccharides (LPSs) and inhibiting the formation of the TLR4/MD-2 complex, which elucidates their potential anti-inflammatory mechanism. Moreover, environmental factors significantly influenced the accumulation of phenolic acids in dandelions, with temperature, precipitation, soil pH, and altitude showing correlations with the content variation of major phenolic acids. These findings provide a scientific basis for determining the optimal harvesting period of dandelion leaves, and offer new insights into the anti-inflammatory mechanisms of phenolic acids. Full article

In this study, a novel hybrid heat source model was developed to simulate the welding temperature field in the heat-affected zone (HAZ) of X80 pipeline steel. This model replicates welding conditions with high accuracy and allows flexible three-dimensional adjustments to suit various scenarios. Its development involved the innovative integration of microstructural crystallography information with a multi-scale calibration and validation methodology. The methodology focused on three critical aspects: the weld interface morphology, the location of the Ac₁ temperature, and the size of prior austenite grains (PAG). The morphology of the weld interface was calibrated to align closely with experimental observations. The model’s prediction of the Ac₁ location in actual welded joints exhibited a deviation of less than ±0.3 mm. Furthermore, comparisons of reconstructed PAG sizes between thermal simulation samples and actual HAZ samples revealed minimal discrepancies (5 μm). Validation results confirmed that the calibrated model accurately describes the welding temperature field, with reconstructed PAG size differences between simulation and experimental results being less than 9 μm. These findings validate the accuracy of the calibrated model in predicting welding temperature fields. This research introduces a novel framework for the development of heat source models, offering a robust foundation for improving welding performance and controlling microstructure in different regions during the welding process of high-strength low-alloy (HSLA) steel. Full article

The forest musk deer (Moschus berezovskii) and Siberian roe deer (Capreolus pygargus) are browsers with a broad sympatric distribution in North and Southwest China. However, little is known about their spatial utilization of microhabitats and habitats. This study, conducted on Huanglong Mountain in China, analyzed the defecation site distribution, indicating preferences of forest musk deer and Siberian roe deer for their habitat demands. Using generalized linear mixed models (GLMMs), we compared the defecation site preferences of both species and further examined their spatial utilization patterns. The results indicated that the primary factors influencing defecation site preferences for forest musk deer were slope (15.79%), elevation (4.26%), herbaceous cover (19.93%), herb height (33.73%), and tree diversity (15.64%). Conversely, for Siberian roe deer, elevation (54.63%) and herbaceous cover (29.31%) were the key factors. Significant differences were found in elevation (p < 0.001) and herbaceous diversity (p < 0.01) between the defecation sites of the two species, with additional notable differences in slope position, tree diversity, and average tree height (p < 0.05). Furthermore, forest musk deer primarily utilized broadleaf forests, coniferous forests, mixed conifer-broadleaf forests, and sparse woodlands. In contrast, Siberian roe deer utilized broadleaf forests, sparse woodlands, and coniferous forests, showing a significant difference (p = 0.01). These findings suggest distinct spatial ecological segregation between forest musk deer and Siberian roe deer regarding their microhabitat preferences and vegetation type utilization at the habitat scale. Full article

In this study, finite element software was used to simulate seepage at the core scale, the stress sensitivity of the shale core of the stripe layer and fractures was evaluated, and the production optimization design of reservoir C in block B of the oilfield under different fracturing parameters and wellbore parameters was simulated. The coupled finite element model of reservoir seepage stress was established; the pore elasticity model was used to determine the reservoir deformation; the seepage followed Forchheimer’s law and Darcy’s law; and finally, the liquid production was calculated to optimize the production plan. The results showed that the permeability under the same stress conditions increased nonlinearly with the increase in the striatal angle at the core scale, the permeability under the same effective stress conditions decreased gradually with the increase in the shale/fringe thickness ratio, and the elastic modulus and Poisson’s ratio of the proppant decreased. The permeability stress sensitivity was stronger. In the reservoir-scale model, the production pressure difference was the most significant factor affecting shale oil production, followed by the number of fractures and the length of the horizontal zone wellbore, and the elastic modulus of the proppant and Poisson’s ratio had the least impact on production. Full article

Deep sea water (DSW) is a globally utilized source of renewable energy and other resources. To understand the characteristics of DSW resources in the South China Sea, in July 2022, the Guangzhou Marine Geological Survey (GMGS) investigated temperature, salinity, pH, dissolved oxygen (DO), inorganic salts (DIN, PO₄³⁻-P, and SiO3-Si), heavy metals (Hg, Pb, As, and Cd), trace elements (Cu, Zn, Fe, Mn, Ni, Se, and Mo), and other related indicators. The results of this investigation elucidate the horizontal and vertical changes in the physical and chemical properties of deep sea water in the Xisha Sea. The surface seawater quality in Xisha was found to be excellent and to meet first-class seawater survey standards. However, the concentrations of various nutrient salts in the surface layer were relatively low. As the seawater depth increased, different trace elements and heavy metals exhibited variations, and the concentrations of various nutrients also gradually increased. Full article

In the process of driving, the steering, braking, and driving conditions and different road conditions affect the vibration characteristics of the vehicle in the vertical, roll, and pitch directions. These factors greatly impact the riding comfort of the vehicle. Among them, the uneven distribution of vertical load between the left and right or the front and rear suspension is one of the important factors affecting the performance indicators of the vehicle’s roll angle acceleration and pitch angle acceleration. In order to improve the ride comfort of the vehicle in vertical, roll, and pitch motion, the inerter is introduced in this paper to form a new type of suspension structure with the “spring-damping” base element, inertial suspension. It breaks away from the traditional “spring-damping” base element of the inherent suspension structure. In this paper, the mechatronic inerter is taken as the actual controlled object, and the inertial suspension structure is considered as the controlled model based on the dynamic surface control theory and the pseudo-inverse matrix principle. Thus, the coordinated control of the inertial suspension can be achieved. Under random road input, compared with passive suspension, the ride comfort performance indicators of the vehicle with inertial suspension based on dynamic surface control are significantly improved. Finally, a Hardware-in-the-Loop (HiL) test of the controller based on dynamic surface control is carried out to verify that the performance of the vehicle inertial suspension using the dynamic surface control algorithm had improved in terms of vehicle ride comfort. The error between the experimental results and the simulation results is about 8%, which verifies the real-time performance and effectiveness of the dynamic surface controller in the real controller. Full article