Search Results (3,520)

To address the critical challenges posed by the complex coastal climate on the external insulation of electrical equipment, research into the prediction of the surface arc inception voltage of epoxy resin under multiple conditions is of great significance for preventing failures and guiding operations and maintenance. In this regard, we propose a prediction method for surface arc inception voltage based on grid search-optimized support vector regression (GS-SVR). Using a 21-dimensional electric field feature set along the shortest inter-electrode path as model input, high-accuracy prediction of surface arc inception voltage under complex conditions is achieved. The results demonstrate that the model accurately predicts surface arc inception voltage with limited samples, achieving a mean absolute percentage error (MAPE) of 6.24%. Furthermore, the non-uniform coefficient-based dataset partitioning method improves prediction accuracy compared to random partitioning, with the lowest MAPE of only 2.39%. The findings provide theoretical and technical support for improving the anti-pollution flashover and anti-condensation performance of epoxy resin insulating materials. Full article

Background/Objectives: Prematurity is a significant global health concern, often associated with neurodevelopmental challenges. Solute Carrier Family 6 Member 4 (SLC6A4), the gene encoding the serotonin transporter, a key component in serotonin reuptake in the synaptic cleft, plays a key role in stress response and neurodevelopment. Epigenetic regulation of stress-related genes, such as SLC6A4, influences neonatal stress adaptation and developmental outcomes. This study aimed to quantify and compare DNA methylation levels at 13 CpG sites in the promoter region of the SLC6A4 gene between preterm and term neonates at three time points. Methods: A cohort of 46 preterm infants and a cohort of 49 full-term infants were analyzed. Blood samples collected at birth (D0), the fifth day (D5), and the thirtieth day (D30) were used to analyze DNA methylation, using bisulfite conversion and pyrosequencing. Results: Significant differences in SLC6A4 methylation were observed. At D0, CpGs 12 and 13 showed higher methylation in preterm infants. CpG 9 showed lower methylation in preterm infants at D5. Extremely preterm infants had the highest values of methylation at the three time points. Longitudinal mixed-effects analysis revealed distinct temporal patterns between groups. Total and site-specific methylation at CpGs 2, 8, and 9 increased over time in full-term infants, while methylation remained stable over time in very preterm and extremely preterm infants. Conclusions: This study reveals significant differences in SLC6A4 methylation between very preterm, extremely preterm, and full-term infants, highlighting the impact of prematurity and early-life stress on the epigenome. These findings contribute to improving our understanding of the epigenetic mechanisms shaping neurodevelopment and stress adaptation in neonates. Full article

Thinopyrum intermedium (c.n. intermediate wheatgrass), marketed under the trade name Kernza, is a promising species for perennial grain production based on seed size, ease of threshing, resistance to shattering, and grain quality. Although numerous generations of breeding for seed yield have been completed, the impact of selection on non-target traits is unknown. Here, we evaluated structural and functional changes brought about by selection for seed yield over a sequence of nine selection cycles (C0 to C9). In two experiments under semi-controlled environmental conditions, we compared gas exchange (A, E, gs, and A/Ci curves), leaf and root morphology, and the structure of seedlings from 10 generations. We found that the selection for yield throughout cycles indirectly changed the leaf structure (leaf size, leaf thickness, and leaf anatomy) and physiology (carbon acquisition and transpiration per unit area), with later cycles showing larger leaves with higher rates of CO₂ assimilation and transpiration. Changes in root structure followed similar trends: selection resulted in longer, more branched, and finer roots. These changes in non-target traits are linked to resource-use strategies and to ecosystem services provided by Kernza. Understanding how the domestication of perennial grains impacts non-target traits will aid in the design of integrated breeding programs for Kernza and other perennial grain crops. Full article

Glycolytic potential (GP) is an important index for evaluating meat quality in the pig industry, since high muscle glycogen content generally leads to rapid postmortem glycolysis, which contributes to low meat quality. The natural differences in meat quality between Chinese local pigs (good meat quality) and Western pigs (standard meat quality) make them the ideal models for glycolysis research. Here, we investigated the mechanisms of glycolysis through comparing transcriptome and metabolome data of biceps femoris (BF) muscle between Jinhua (JH) and Landrace × Yorkshire (LY) pigs at different ages. In this research, JH pigs exhibited lower intramuscular glycogen content than LY pigs throughout the growth period (p < 0.05). Increased phosphorylated glycogen synthase (p-GS) expression indicated reduced glycogenesis capacity in JH pigs. Pathway enrichment revealed that the differentially expressed genes (DEGs) were highly enriched in glycolysis, glycogenesis, and TCA cycle pathways, but these metabolic pathways were suppressed in JH pigs. Metabolomic analysis identified increased lipids and amino acids, but carbohydrate metabolites were decreased in JH pigs. Through integrating transcriptome and metabolome data, VASH1 was identified as a biomarker of muscle glycolysis. Mechanistically, VASH1 knockdown promoted glucose metabolism through enhancing glycolysis and glycogenesis via the AMPK signaling pathway. Our findings provided novel insights into the genetic basis of meat quality and identify VASH1 as a potential target for genetic selection to improve muscle glycolytic level and pork quality. Full article

Soil water availability and nitrogen (N) deposition critically influence biogenic volatile organic compound (BVOC) emissions, thereby affecting atmospheric chemistry. However, their differential short- and long-term effects remain unclear. Here, Ormosia pinnata and Pinus massoniana seedlings were exposed to three water regimes (moderate drought, MD; normal irrigation, NI; near-saturated irrigation, NSI) and two nitrogen (N0; 0 kg N ha⁻¹ yr⁻¹; N80; 80 kg N ha⁻¹ yr⁻¹) treatments for 20 months. Branch-level BVOC emissions and leaf physiological and biochemical traits were examined after 8 months (short term) and 16 months (long term). In the short term, P. massoniana predominantly emitted α-pinene, β-pinene, and γ-terpinene, whereas O. pinnata emitted isoprene (ISO). After prolonged exposure, ISO became the dominant in both species. Short-term MD and NSI conditions stimulated ISO emissions in O. pinnata, with N80 addition further amplifying this effect. In contrast, long-term treatments tended to suppress ISO emissions in O. pinnata, particularly under N80. Short-term water treatments had no significant effect on monoterpene (MT) emissions in P. massoniana. Under long-term water treatments, N80 suppressed ISO emissions; nevertheless, ISO emission rates (ISOrate) progressively increased with increasing soil water availability. Although leaf intercellular CO₂ concentration (Ci), stomatal conductance (g_s), and photosynthesis-related enzymes exhibited partial correlations with BVOC emissions, an overall decoupling between leaf traits and emission patterns was evident. Our findings demonstrate the significant changes in both BVOC composition and emission magnitudes under the joint effects of water availability and nitrogen deposition, providing important implications for improving regional air quality modeling and BVOC emission predictions. Full article

Gerstmann syndrome (GS) is characterised by the tetrad of agraphia, acalculia, finger agnosia, and right-left disorientation, which was first described by Josef Gerstmann in 1924 and is conventionally linked to lesions of the dominant angular gyrus. Contemporary neuroimaging and lesion mapping research indicates that a more dispersed parietal and occipito-temporal network may be involved. Bilateral parietal lobe infarcts are uncommon and usually arise from embolic events or small artery pathology, frequently resulting in multifocal cognitive and perceptual impairments. A 52-year-old male presented with acute confusion, perseverative speech, and an inability to follow commands. The neurological examination indicated the presence of the complete Gerstmann tetrad. The Magnetic Resonance Imaging (MRI brain) revealed bilateral parieto-occipital infarcts, with greater severity on the left, indicative of ischaemia in the territory of the posterior cerebral artery (PCA). The medical team provided supportive care and implemented secondary stroke prevention, leading to partial neurocognitive recovery over a period of three weeks. This case highlights a rare presentation of Gerstmann syndrome due to bilateral parieto-occipital infarcts and emphasises that the syndrome can arise from bilateral or widespread parietal injury rather than lesions limited to the angular gyrus. The prompt identification of the Gerstmann constellation helps localise the lesion, enhances diagnostic accuracy, and aids in rehabilitation planning. Full article

Water stress is the main abiotic factor that limits the development and commercial quality of ornamental plants, such as Zinnia elegans. This study aimed to evaluate the ability of exogenous melatonin (MEL) to attenuate the deleterious effects of water deficit by modulating stomatal physiological, biochemical and structural parameters. Z. elegans plants were subjected to four water regimes (80% FC, 20% FC, early stress and late stress) with (1.0 mM) and without MEL application. Severe water stress (20% FC) drastically reduced the rate of CO₂ assimilation (A) by 43.81% and stomatal conductance (gs) by 68.96%. However, the application of MEL significantly mitigated this damage, resulting in an increase in A of 26.99% gs of 43.75%, and relative water content of 28% in plants under severe stress compared with those in untreated stressed plants. The mechanism of action of MEL involves the modulation of stomatal motion and, as suggested, the promotion of osmotic fit and the protection of membrane integrity and photochemical efficiency. Exogenous melatonin acts as an effective bioregulator, improving the tolerance of Z. elegans to water deficit and sustaining its physiological performance and ornamental potential under stress conditions. Full article

With growing demand for functional foods, mushroom-based ingredients are gaining popularity. The typical white mushroom (Agaricus bisporus) is particularly valued for its bioactive compounds and shows promise as a nutritional enhancer in widely consumed products, such as chocolate. This study examined the fortification of dark, milk, and white chocolates with freeze-dried, sous-vide processed A. bisporus powder at 4%, 6%, and 8% levels. Analyses focused on protein content, dietary fiber, essential minerals, texture, and sensory characteristics. Mushroom addition notably improved nutritional values. In white chocolate, protein increased from 6.04% to 8.92%, while dark chocolate with 8% fortification reached 13.25%, compared to 11.09% in the control. The magnesium content also increased significantly, from 2579 mg/kg to 3184 mg/kg. Total dietary fiber also showed a significant improvement. Texture analysis revealed a reduction in firmness, with the 8% A. bisporus powder fortified dark chocolate formulation softening from 24,685 g·s to 10,633 g·s. Despite these changes, sensory evaluation confirmed that taste and appearance remained acceptable. Overall, incorporating A. bisporus powder into chocolate improved its nutritional profile while introducing moderate changes to texture. These findings highlight its potential as a functional ingredient in the development of healthier confectionery products. Full article

Soil alkalinity severely restricts the cultivation of Lupinus angustifolius, a valuable legume. Wild soybean (Glycine soja) is a leguminous plant with extremely strong alkaline resistance (pH 8.5). Transferring the alkali-tolerant genes from wild soybeans into lupinus can effectively enhance the alkali tolerance. In this study, we combined transcriptome profiling and genetic transformation to elucidate the molecular basis of alkaline stress response in lupinus. RNA-seq analysis of root tips under acid (HCl, pH 4.0) and alkali (NaHCO₃, pH 8.5) stress revealed 104,353 annotated unigenes, with differential expression patterns highlighting enrichment in cellular component, binding, and catalytic activity categories. KEGG pathway analysis indicated that early responses involved ribosome-related pathways, while later stages activated plant hormone signaling and MAPK pathways. Notably, no homeodomain-leucine zipper (HD-Zip) family genes were identified in the lupinus genome. Therefore, we transferred GsHZ4, an alkali-resistant HD-Zip transcription factor from wild soybean into lupinus hairy roots via Agrobacterium rhizogenes-mediated transformation. Overexpression of GsHZ4 significantly enhanced antioxidant enzyme activities (CAT, POD, and SOD) and reduced malondialdehyde content under NaHCO₃ stress. Furthermore, the promoter of GsHZ4 expression was strongly induced by indole-3-acetic acid (IAA). Key alkali-responsive genes (LaKIN, LaMYB34, LaDnaJ1, LaDnaJ20, LaNAC22, and LaNAC35) were upregulated in transgenic lines, suggesting that GsHZ4 integrates into the endogenous stress-regulation network. Our findings demonstrate that heterologous expression of GsHZ4 can enhance alkaline tolerance of lupinus, providing a novel strategy for breeding stress-resistant varieties and expanding lupinus cultivation in saline–alkali soils. Full article

Nitrogen assimilation is vital for apple growth, yield, and quality, with nitrate reductase (NIA), nitrite reductase (NIR), glutamine synthetase (GS), and glutamate synthase (GOGAT) serving as key regulatory enzymes. This study systematically identified these four gene families in apple (Malus domestica) through genome-wide analysis and examined their expression patterns under nitrate treatment. In total, 13 genes were identified, 2 MdNIAs, 1 MdNIR, 7 MdGSs, and 3 MdGOGATs, with gene lengths ranging from 2577 to 27736 base pairs (bp); MdGLT1A had the longest coding sequence (6627 bp). The encoded proteins contained 355–2208 amino acids, with predicted isoelectric points (pIs) between 5.55 and 6.63. Subcellular localization analysis predicted distinct compartmentalization: MdNIA1A in peroxisomes; MdGS1 in the cytosol; MdNIR1, MdGS2, and MdGLU1 in chloroplasts; and MdGLT1 in mitochondria/chloroplasts. Functional site prediction revealed multiple phosphorylation and glycosylation sites, with ATP/GTP-binding motifs present only in certain MdGOGAT proteins. Protein interaction analysis suggested close associations among these genes and possible interactions with NRT2.1/2.2. Chromosomal mapping showed their distribution across eight chromosomes, while promoter analysis identified diverse cis-acting regulatory elements (e.g., ABRE and G-box). Under nitrate treatment (0–12 h), these genes exhibited distinct expression dynamics: MdNIA1A and B were rapidly induced (0–6 h) and maintained high expression; MdNIR1 peaked at 6 h and then declined; MdGS1.1B was activated after 6 h; and MdGS2A, MdGLU1, and MdGLT1A/B peaked at 6 h before decreasing. Therefore, these results elucidate the structural and functional divergence of nitrogen assimilation genes in apple and provide a basis for understanding nitrogen utilization mechanisms and developing nitrogen-efficient breeding strategies. Full article

Docosahexaenoic acid (DHA), an omega-3 polyunsaturated fatty acid essential for human health, is primarily produced at scale using Schizochytrium sp. Mutagenesis-based strain improvement has increased DHA yields, but the genetic and metabolic mechanisms underlying high productivity remain poorly understood. Here, we conducted the comparative whole-genome sequencing and transcriptomic profiling of a high-DHA-yielding mutant strain (HS01) and its parental strain (GS00). The GS00 genome assembly spans 62.4 Mb and encodes 14,886 predicted genes. Functional annotation highlighted pathways involved in central metabolism, saturated fatty acid (SFA) synthesis, and polyunsaturated fatty acid (PUFA)/DHA biosynthesis. Comparative genomics identified 40 insertions/deletions and 396 single-nucleotide polymorphisms between HS01 and GS00, including mutations in the coding and regulatory regions of key metabolic genes. Transcriptomic analysis revealed extensive metabolic reprogramming in HS01, including the upregulation of glycolysis and tricarboxylic acid (TCA) cycle genes, along with a distinct fatty acid profile and the altered expression of fatty acid metabolism genes compared with GS00. Collectively, the integrated genomic and transcriptomic analyses not only pinpointed specific mutations potentially associated with the HS01 high-DHA phenotype but also revealed substantial transcriptional and metabolic remodeling, providing valuable insights into the mechanisms that drive enhanced DHA biosynthesis. Full article

This study introduces the Graph-Structured Physics-Informed DeepONet (GS-PI-DeepONet), a novel neural network framework designed to address the challenges of solving parametric Partial Differential Equations (PDEs) in structural analysis, particularly for problems with complex geometries and dynamic boundary conditions. By integrating Graph Neural Networks (GNNs), Deep Operator Networks (DeepONets), and Physics-Informed Neural Networks (PINNs), the proposed method employs graph-structured representations to model unstructured Finite Element (FE) meshes. In this framework, nodes encode physical quantities such as displacements and loads, while edges represent geometric or topological relationships. The framework embeds PDE constraints as soft penalties within the loss function, ensuring adherence to physical laws while reducing reliance on large datasets. Extensive experiments have demonstrated the GS-PI-DeepONet’s superiority over traditional Finite Element Methods (FEMs) and standard DeepONets. For benchmark problems, including cantilever beam bending and Hertz contact, the model achieves high accuracy. In practical applications, such as stiffness analysis of a recliner mechanism and strength analysis of a support bracket, the framework achieves a 7–8 speed-up compared to FEMs, while maintaining fidelity comparable to FEM, with R² values reaching up to 0.9999 for displacement fields. Consequently, the GS-PI-DeepONet offers a resolution-independent, data-efficient, and physics-consistent approach for real-time simulations, making it ideal for rapid parameter sweeps and design optimizations in engineering applications. Full article

Valve internal leakage in thermal power stations exhibits a strong concealed nature. If it cannot be discovered and predicted of development trend in time, it will affect the safe and economical operation of plant equipment. This paper proposed an intelligent identification method for valve internal leakage that integrated an Improved Kepler Optimization Algorithm (IKOA) with Support Vector Regression (SVR). The Kepler Optimization Algorithm (KOA) was improved using the Sobol sequence and an adaptive Gaussian mutation strategy to achieve self-optimization of the key parameters in the SVR model. A multi-step sliding cross-validation method was employed to train the model, ultimately yielding the IKOA-SVR intelligent identification model for valve internal leakage quantification. Taking the main steam drain pipe valve as an example, a simulation case validation was carried out. The calculation example used Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and determination coefficient (R²) as performance evaluation metrics, and compared and analyzed the training and testing dataset using IKOA-SVR, KOA-SVR, Particle Swarm Optimization (PSO)-SVR, Random Search (RS)-SVR, Grid Search (GS)-SVR, and Bayesian Optimization (BO)-SVR methods, respectively. For the testing dataset, the MSE of IKOA-SVR is 0.65, RMSE is 0.81, MAE is 0.49, and MAPE is 0.0043, with the smallest values among the six methods. The R² of IKOA-SVR is 0.9998, with the largest value among the six methods. It indicated that IKOA-SVR can effectively solve problems such as getting stuck in local optima and overfitting during the optimization process. An Out-Of-Distribution (OOD) test was conducted for two scenarios: noise injection and Region-Holdout. The identification performance of all six methods decreased, with IKOA-SVR showing the smallest performance decline. The results show that IKOA-SVR has the strongest generalization ability and robustness, the best effect in improving fitting ability, the smallest identification error, the highest identification accuracy, and results closer to the actual value. The method presented in this paper provides an effective approach to solve the problem of intelligent identification of valve internal leakage in thermal power station. Full article

Background/Objectives: Compartmentalized glucose metabolism in the brain contributes to neuro-metabolic stability and shapes hypothalamic control of glucose homeostasis. Glucose transporter-2 (GLUT2) is a plasma membrane glucose sensor that exerts sex-specific control of hypothalamic astrocyte glucose and glycogen metabolism. Aging causes counterregulatory dysfunction. Methods: The current research used Western blot and HPLC–electrospray ionization–mass spectrometry to investigate whether aging affects the GLUT2-dependent hypothalamic astrocyte metabolic sensor, glycogen enzyme protein expression, and glycogen mass according to sex. Results: The data document GLUT2-dependent upregulated glucokinase (GCK) protein in glucose-deprived old male and female astrocyte cultures, unlike GLUT2 inhibition of this protein in young astrocytes. Glucoprivation of old male and female astrocytes caused GLUT2-independent downregulation of 5′-AMP-activated protein kinase (AMPK) protein, indicating loss of GLUT2 stimulation of this protein with age. This metabolic stress also caused GLUT2-dependent suppression of phospho-AMPK profiles in each sex, differing from GLUT2-mediated glucoprivic enhancement of activated AMPK in young male astrocytes and phospho-AMPK insensitivity to glucoprivation in young female cultures. GS and GP isoform proteins were refractory to glucoprivation of old male cultures, contrary to downregulation of these proteins in young glucose-deprived male astrocytes. Aging elicited a shift from GLUT2 inhibition to stimulation of male astrocyte glycogen accumulation and caused gain of GLUT2 control of female astrocyte glycogen. Conclusions: The outcomes document sex-specific, aging-related alterations in GLUT2 control of hypothalamic astrocyte glucose and ATP monitoring and glycogen mass and metabolism. These results warrant future initiatives to assess how these adjustments in hypothalamic astrocyte function may affect neural operations that are shaped by astrocyte–neuron metabolic partnership. Full article

Nickel–tungsten carbide (Ni/WC) multi-pass fused cladding layers with different cerium (IV) oxide (CeO₂) contents were applied to Cr12MoV cold work tool steel surfaces using the coaxial powder feeding method for laser cladding. Scanning electron microscopy, energy spectrum analysis, X-ray diffraction, and wear experiments were conducted to study how adding CeO₂ to change the properties of WC-reinforced Ni-base composite coatings in turn alters the microstructure and properties of Cr12MoV cold work tool steel. The results show that laser cladding is effective when the process parameters are as follows: a power of 1500 W, a 24 mm defocusing distance, a 6 mm/s scanning speed, a 5 mm spot diameter, and a powder delivery of 0.1 g/s. Laser-fused cladding coatings are mainly composed of dendrites, crystalline cells, strips, and bulk microstructures. The addition of CeO₂ is effective at improving the microstructure and morphology of the coating—the size and distribution of the reinforcing phase change very significantly, and the shape changes from irregular and lumpy to spherical. With a 2% CeO₂ content, the enhanced phase, now spherical and white, is more diffusely distributed in the tissue. The maximum microhardness of the composite-coated specimen after the addition of CeO₂ is about 986 HV, which is approximately 20% higher than the hardness of the composite coating with no CeO₂ added. Full article